Meta-analysis of 74,046 individuals identifies 11 new … · 2014-01-30 · Supplementary...

Supplementary Information

Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci forAlzheimer’s disease

Jean-Charles Lambert, Carla A Ibrahim-Verbaas, Denise Harold, Adam C Naj, Rebecca Sims, Céline Bellenguez,Gyungah Jun, Anita L DeStefano, Joshua C Bis, Gary W Beecham, Benjamin Grenier-Boley, Giancarlo Russo,Tricia A Thornton-Wells, Nicola Jones, Albert V Smith, Vincent Chouraki, Charlene Thomas, M Arfan Ikram,Diana Zelenika, Badri N Vardarajan, Yoichiro Kamatani, Chiao-Feng Lin, Amy Gerrish, Helena Schmidt, BrianKunkle, Melanie L Dunstan, Agustin Ruiz, Marie-Thérèse Bihoreau, Seung-Hoan Choi, Christiane Reitz, FlorencePasquier, Paul Hollingworth, Alfredo Ramirez, Olivier Hanon, Annette L Fitzpatrick, Joseph D Buxbaum,Dominique Campion, Paul K Crane, Clinton Baldwin, Tim Becker, Vilmundur Gudnason, Carlos Cruchaga, DavidCraig, Najaf Amin, Claudine Berr, Oscar L Lopez, Philip L De Jager, Vincent Deramecourt, Janet A Johnston,Denis Evans, Simon Lovestone, Luc Letenneur, Francisco J Morón, David C Rubinsztein, Gudny Eiriksdottir,Kristel Sleegers, Alison M Goate, Nathalie Fiévet, Matthew J Huentelman, Michael Gill, Kristelle Brown, M IlyasKamboh, Lina Keller, Pascale Barberger-Gateau, Bernadette McGuinness, Eric B Larson, Robert Green, AmandaJ Myers, Carole Dufouil, Stephen Todd, David Wallon, Seth Love, Ekaterina Rogaeva, John Gallacher, Peter StGeorge-Hyslop, Jordi Clarimon, Alberto Lleo, Anthony Bayer, Debby W Tsuang, Lei Yu, Magda Tsolaki, PaolaBossù, Gianfranco Spalletta, Petroula Proitsi, John Collinge, Sandro Sorbi, Florentino Sanchez Garcia, Nick CFox, John Hardy, Maria Candida Deniz Naranjo, Paolo Bosco, Robert Clarke, Carol Brayne, Daniela Galimberti,Michelangelo Mancuso, Fiona Matthews, EADI, GERAD, ADGC, CHARGE, Susanne Moebus, Patrizia Mecocci,Maria Del Zompo, Wolfgang Maier, Harald Hampel, Alberto Pilotto, Maria Bullido, Francesco Panza, PaoloCaffarra, Benedetta Nacmias, John R Gilbert, Manuel Mayhaus, Lars Lannfelt, Hakon Hakonarson, SabrinaPichler, Minerva M Carrasquillo, Martin Ingelsson, Duane Beekly, Victoria Alvarez, Fanggeng Zou, OttoValladares, Steven G Younkin, Eliecer Coto, Kara L Hamilton-Nelson, Wei Gu, Cristina Razquin, Pau Pastor,Ignacio Mateo, Michael J Owen, Kelley M Faber, Palmi V Jonsson, Onofre Combarros, Michael C O’Donovan,Laura B Cantwell, Hilkka Soininen, Deborah Blacker, Simon Mead, Thomas H Mosley Jr, David A Bennett,Tamara B Harris, Laura Fratiglioni, Clive Holmes, Renee FAG de Bruijn, Peter Passmore, Thomas J Montine,Karolien Bettens, Jerome I Rotter, Alexis Brice, Kevin Morgan, Tatiana M Foroud, Walter A Kukull, DidierHannequin, John F Powell, Michael A Nalls, Karen Ritchie, Kathryn L Lunetta, John SK Kauwe, Eric Boerwinkle,Matthias Riemenschneider, Mercè Boada, Mikko Hiltunen, Eden R Martin, Reinhold Schmidt, Dan Rujescu,Li-San Wang, Jean-François Dartigues, Richard Mayeux, Christophe Tzourio, Albert Hofman, Markus M Nöthen,Caroline Graff, Bruce M Psaty, Lesley Jones, Jonathan L Haines, Peter A Holmans, Mark Lathrop, Margaret APericak-Vance, Lenore J Launer, Lindsay A Farrer, Cornelia M van Duijn, Christine Van Broeckhoven, ValentinaMoskvina, Sudha Seshadri, Julie Williams, Gerard D Schellenberg, Philippe Amouyel.

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Nature Genetics: doi:10.1038/ng.2802

Page

Supplementary Figure 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Q-Q plots (a) at the exclusion of the APOE locus (chr19:44,000,000-47,000,000) and (b) at the exclusion of the APOE locusand the genome-wide significant loci.

Supplementary Figure 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6Regional plots for the (a) CR1 (rs6656401) and (b) BIN1 (rs6733839) loci. SNPs in purple are the best associated SNPs afterstage 1 and stage 2.

Supplementary Figure 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Regional plots for the (a) CD2AP (rs10948363) and (b) EPHA1 (rs11771145) loci. SNPs in purple are the best associatedSNPs after stage 1 and stage 2.

Supplementary Figure 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8Regional plots for the (a) MS4A6A (rs983392) and (b) PICALM (rs10792832) loci. SNPs in purple are the best associatedSNPs after stage 1 and stage 2.

Supplementary Figure 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Regional plots for the (a) ABCA7 (rs4147929 and (b) CD33 (rs3865444) loci. SNPs in purple are the best associated SNPsafter stage 1 and stage 2.

Supplementary Figure 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Regional plots for the (a) HLA-DRB1/DRB5 (rs9271192) and (b) SORL1 (rs11218343) loci. SNPs in purple are the bestassociated SNPs after stage 1 and stage 2.

Supplementary Figure 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Regional plots for the (a) SCL24A4 (rs10498633) and (b) DGS2 (rs8093731) loci. SNPs in purple are the best associated SNPsafter stage 1 and stage 2.

Supplementary Figure 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12Regional plots for the (a) INPP5D (rs35349669) and (b) MEF2C (rs190982) loci. SNPs in purple are the best associated SNPsafter stage 1 and stage 2.

Supplementary Figure 9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Regional plots for the (a) NME8 (rs2718058) and (b) ZCWPW1 (rs1476679) loci. SNPs in purple are the best associated SNPsafter stage 1 and stage 2.

Supplementary Figure 10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Regional plots for the (a) CELF1 (rs10838725) and (b) FERMT2 (rs17125944) loci. SNPs in purple are the best associatedSNPs after stage 1 and stage 2.

Supplementary Figure 11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Regional plot for the CASS4 (rs7274581) locus. SNP in purple is the best associated SNP after stage 1 and stage 2.

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Supplementary Figure 12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Forest plots for (a) rs6656401 (CR1), (b) rs6733839 (BIN1), (c) rs10948363 (CD2AP), (d) rs11771145 (EPHA1), (e) rs9331896(CLU) and (f) rs983392 (MS4A6A).

Supplementary Figure 13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Forest plots for (a) rs10792832 (PICALM), (b) rs4147929 (ABCA7) and (c) rs3865444 (CD33).

Supplementary Figure 14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Forest plots for (a) rs9271192 (HLA-DRB5/HAL-DRB1), (b) rs28834970 (PTK2B), (c) rs11218343 (SORL1), (d) rs10498633(SCL24A4) and (e) rs8093731 (DSG2).

Supplementary Figure 15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Forest plots for (a) rs35349669 (INPP5D), (b) rs190982 (MEF2C), (c) rs2718058 (NME8), (d) rs1476679 (ZCWPW1), (e)rs10838725 (CELF1) and (f) rs17125944 (FERMT2).

Supplementary Figure 16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Forest plot for rs7274581 (CASS4).

Supplementary Figure 17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Regional association of the PTK2B/CLU SNPs with AD risk (a) before and (b) after conditional analyses (adjustment for thebest CLU signal (rs9331896)).

Supplementary Figure 18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Evaluation of genotyping biases by the comparison of the minor allele frequency (MAF) observed in stage 2 control samplesand the 1000 genome data set (European ancestry individuals). Y-axis shows -log(p-value) of the allelic test computed bypermutation (see Supplementary note). The X-axis was cut so that only SNPs with MAF difference between -0.15 and 0.15are shown. SNPs are coloured according to their MAF in the stage 2 data. Horizontal dashed red line shows p-value cutoff

of 1 × 10−5 and vertical dashed red line shows the corresponding MAF difference cutoff. All SNPs with p-value lower than1 × 10−5 were excluded from the analysis.

Supplementary Table 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Full description of the different datasets from each consortium.

Supplementary Table 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24General description of the imputation and meta-analysis processes and number of SNPs available after each step.

Supplementary Table 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Summary of eQTL annotation for the loci reaching genome-wide significance in the combined stage 1 and stage 2.

Supplementary Table 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26Summary of stage 1, stage 2 and overall meta-analyses for SNPs showing suggestive association with AD risk after stage 1and stage 2.

Supplementary Table 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Conditional analysis of the two best associated CLU and PTK2B SNPs in stage 2.

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Supplementary Table 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28Description of the population attributable/preventive fractions for the GWAS-defined genes in stage 2.

Supplementary Table 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Full description of the GERAD stage 1 datasets.

Supplementary Table 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Full description of the stage 2 datasets by centre.

Supplementary Table 9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Test of missingness difference between cases and controls across the stage 2 samples.

Supplementary Table 10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Description of the stage 2 samples before and after quality control according to the country of origin.

Supplementary Note . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Full I-GAP datasets description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

EADI consortium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

ADGC consortium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

CHARGE consortium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

GERAD consortium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

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Supplementary Figure 1Q-Q plots (a) at the exclusion of the APOE locus (chr19:44,000,000-47,000,000) and

(b) at the exclusion of the APOE locus and the genome-wide significant loci

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Supplementary Figure 2Regional plots for the (a) CR1 (rs6656401) and (b) BIN1 (rs6733839) loci

SNPs in purple are the best associated SNPs after stage 1 and stage 2

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207.5 207.6 207.7 207.8 207.9Position on chr1 (Mb)

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r2

BIN1 CYP27C1 ERCC3

MAP3K2

127.7 127.8 127.9 128 128.1Position on chr2 (Mb)

6


Supplementary Figure 3Regional plots for the (a) CD2AP (rs10948363) and (b) EPHA1 (rs11771145) loci


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bination rate (cM/M

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rs10948363

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0.2

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0.8

r2

GPR110 TNFRSF21 CD2AP

GPR111

GPR115 OPN5 C6orf138

47 47.2 47.4 47.6 47.8Position on chr6 (Mb)

b

0

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0

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bination rate (cM/M

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rs11771145

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0.2

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r2

TAS2R39

TAS2R40

GSTK1

TMEM139

CASP2

CLCN1

FAM131B

ZYX

EPHA1

LOC285965

TAS2R60

TAS2R41

CTAGE15P FAM115C

142.9 143 143.1 143.2 143.3Position on chr7 (Mb)

7


Supplementary Figure 4Regional plots for the (a) MS4A6A (rs983392) and (b) PICALM (rs10792832) loci


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bination rate (cM/M

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0.2

0.4

0.6

0.8

r2

PATL1

OR10V1

STX3

MRPL16

GIF

TCN1

PLAC1L

MS4A3

MS4A2

MS4A6A MS4A4A

MS4A6E

MS4A7

MS4A14

MS4A5

MS4A1

MS4A12

MS4A13

C11orf64

59.6 59.8 60 60.2 60.4Position on chr11 (Mb)

b

0

5

10

15

0

20

40

60

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100

Recom

bination rate (cM/M

b)

rs10792832

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r2

CREBZF

CCDC89

SYTL2

CCDC83 PICALM EED

C11orf73

CCDC81

ME3


8


Supplementary Figure 5Regional plots for the (a) ABCA7 (rs4147929 and (b) CD33 (rs3865444) loci


a

0

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bination rate (cM/M

b)

rs4147929

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r2

BSG

HCN2

POLRMT

FGF22

RNF126

FSTL3

PRSSL1

PALM

C19orf21

PTBP1

LPPR3

MIR3187

AZU1

PRTN3

ELANE

CFD

C19orf22

KISS1R

ARID3A

WDR18

GRIN3B

C19orf6

CNN2

ABCA7

HMHA1

POLR2E

GPX4

SBNO2

STK11

C19orf26

ATP5D

MIDN

C19orf23

CIRBP

C19orf24

MUM1

NDUFS7

GAMT

DAZAP1

RPS15

APC2

C19orf25

PCSK4

REEP6

PLK5P


b

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bination rate (cM/M

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rs3865444

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r2

KLK7

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CTU1

SIGLEC9

SIGLEC7

SIGLECP3 CD33

C19orf75

IGLON5

VSIG10L

ETFB

CLDND2

NKG7

LIM2

LOC147646

SIGLEC10

LOC100129083

SIGLEC8

51.5 51.6 51.7 51.8 51.9Position on chr19 (Mb)

9


Supplementary Figure 6Regional plots for the (a) HLA-DRB1/DRB5 (rs9271192) and (b) SORL1 (rs11218343) loci


a

0

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4

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10

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bination rate (cM/M

b)

rs9271192

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0.2

0.4

0.6

0.8

r2

ATF6B

FKBPL

PRRT1

PPT2

EGFL8

AGPAT1

RNF5

C6orf10

BTNL2

HLA−DRA

HLA−DRB5

HLA−DRB6

HLA−DRB1

HLA−DQA1

HLA−DQB1

HLA−DQA2

HLA−DQB2

HLA−DOB

TAP2

PSMB8

TAP1

PSMB9

PPP1R2P1

HLA−DMB

HLA−DMA

BRD2

HLA−DOA

HLA−DPA1

HLA−DPB132.2 32.4 32.6 32.8 33

Position on chr6 (Mb)

b

0

2

4

6

8

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0

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60

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100

Recom

bination rate (cM/M

b)

rs11218343

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0.2

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r2

TBCEL

TECTA

SC5DL SORL1


10


Supplementary Figure 7Regional plots for the (a) SCL24A4 (rs10498633) and (b) DGS2 (rs8093731) loci


a

0

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bination rate (cM/M

b)

rs10498633

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●● 0.2

0.4

0.6

0.8

r2

TRIP11

ATXN3

NDUFB1

CPSF2

SLC24A4 RIN3

LGMN

GOLGA5 CHGA

ITPK1


b

0

2

4

6

8

10

0

20

40

60

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100

Recom

bination rate (cM/M

b)

rs8093731

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r2

DSC3

DSC2

DSC1 DSG1

DSG4

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DSG2

TTR

B4GALT6

MCART2 TRAPPC8


11


Supplementary Figure 8Regional plots for the (a) INPP5D (rs35349669) and (b) MEF2C (rs190982) loci


a

0

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bination rate (cM/M

b)

rs35349669

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0.2

0.4

0.6

0.8

r2

GIGYF2

KCNJ13 C2orf82

NGEF

NEU2

INPP5D ATG16L1

SCARNA5

SCARNA6

SAG

DGKD

USP40

UGT1A8

UGT1A10


b

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bination rate (cM/M

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rs190982

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r2

LOC645323

MIR9−2

MEF2C

87.8 88 88.2 88.4 88.6Position on chr5 (Mb)

12


Supplementary Figure 9Regional plots for the (a) NME8 (rs2718058) and (b) ZCWPW1 (rs1476679) loci


a

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bination rate (cM/M

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rs2718058

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0.2

0.4

0.6

0.8

r2

ELMO1 GPR141 NME8

SFRP4

EPDR1

STARD3NL

TARP


b

0

2

4

6

8

10

0

20

40

60

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100

Recom

bination rate (cM/M

b)

rs1476679

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0.2

0.4

0.6

0.8

r2

TRIM4

GJC3

AZGP1

AZGP1P1

ZKSCAN1

ZSCAN21

ZNF3

COPS6

MCM7

MIR25

MIR93

MIR106B

C7orf59

GPC2

STAG3

GATS

PVRIG

SPDYE3

PMS2P1

PILRB

PILRA

ZCWPW1

MEPCE

C7orf47

C7orf61

TSC22D4

C7orf51

AGFG2

SAP25

LRCH4

FBXO24

PCOLCE

MOSPD3

TFR2

ACTL6B

GNB2

GIGYF1

POP7

EPO

ZAN

EPHB4

SLC12A9

TRIP6

SRRT

UFSP1

ACHE99.6 99.8 100 100.2 100.4

Position on chr7 (Mb)

13


Supplementary Figure 10Regional plots for the (a) CELF1 (rs10838725) and (b) FERMT2 (rs17125944) loci


a

0

2

4

6

8

10

0

20

40

60

80

100

Recom

bination rate (cM/M

b)

rs10838725

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0.2

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r2

C11orf49

ARFGAP2

PACSIN3

DDB2

ACP2

NR1H3

MADD

MYBPC3

SPI1

SLC39A13

PSMC3

RAPSN

CELF1

PTPMT1

KBTBD4

NDUFS3

FAM180B

C1QTNF4

MTCH2

AGBL2

FNBP4

NUP160

PTPRJ

47.2 47.4 47.6 47.8 48Position on chr11 (Mb)

b

0

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100

Recom

bination rate (cM/M

b)

rs17125944

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0.2

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r2

TXNDC16

GPR137C

ERO1L

PSMC6

STYX

GNPNAT1 FERMT2 DDHD1


14


Supplementary Figure 11Regional plot for the CASS4 (rs7274581) locus

SNP in purple is the best associated SNP after stage 1 and stage 2

0

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bination rate (cM/M

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0.2

0.4

0.6

0.8

r2

MC3R C20orf108

AURKA

CSTF1

CASS4 C20orf43

GCNT7

C20orf106

C20orf107

TFAP2C


15


Supplementary Figure 12Forest plots for (a) CR1, (b) BIN1, (c) CD2AP, (d) EPHA1, (e) CLU and (f) MS4A6A

aStudy

ADGCCHARGEEADIGERAD

Discovery

AustriaBelgiumFinlandGermanyGreeceHungaryItalySpainSwedenUKUSA

Replication

Combined

OR

1.181.071.211.20

1.17

1.401.231.271.171.550.871.121.271.241.181.11

1.21

1.18

95% CI

(1.12−1.24)(0.95−1.20)(1.09−1.33)(1.07−1.35)

(1.12−1.22)

(1.03−1.90)(1.00−1.51)(1.00−1.61)(1.02−1.34)(0.99−2.43)(0.53−1.41)(0.95−1.32)(1.12−1.44)(1.07−1.43)(0.96−1.45)(0.93−1.33)

(1.14−1.28)

(1.14−1.22)

P

7.73e−15

7.89e−11

5.69e−24

0.6 0.8 1 1.2 1.4 1.6 1.8 2

OR

rs6656401 bStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.221.141.201.23

1.21

1.271.291.111.210.921.191.361.291.231.241.11

1.24

1.22

95% CI

(1.17−1.28)(1.04−1.25)(1.11−1.29)(1.11−1.37)

(1.17−1.25)

(0.99−1.64)(1.08−1.53)(0.92−1.34)(1.08−1.36)(0.64−1.34)(0.78−1.80)(1.19−1.55)(1.17−1.43)(1.09−1.40)(1.05−1.46)(0.96−1.29)

(1.18−1.29)

(1.18−1.25)

P

1.66e−26

3.44e−19

6.94e−44

0.8 1 1.2 1.4 1.6 1.8

OR

rs6733839

cStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.111.051.061.18

1.10

0.991.220.981.131.081.121.121.091.091.140.99

1.09

1.10

95% CI

(1.06−1.16)(0.95−1.15)(0.97−1.15)(1.07−1.31)

(1.07−1.14)

(0.74−1.32)(1.01−1.46)(0.79−1.22)(1.00−1.28)(0.71−1.65)(0.71−1.78)(0.97−1.30)(0.98−1.21)(0.95−1.25)(0.95−1.36)(0.84−1.17)

(1.04−1.15)

(1.07−1.13)

P

3.05e−08

4.11e−04

5.20e−11

0.8 1 1.2 1.4 1.6

OR

rs10948363 dStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.920.870.830.95

0.90

0.821.090.810.851.180.950.850.830.970.991.00

0.90

0.90

95% CI

(0.88−0.96)(0.80−0.96)(0.77−0.90)(0.87−1.04)

(0.87−0.93)

(0.64−1.06)(0.91−1.30)(0.67−0.98)(0.75−0.95)(0.79−1.76)(0.62−1.44)(0.74−0.98)(0.75−0.92)(0.86−1.10)(0.84−1.17)(0.86−1.16)

(0.86−0.95)

(0.88−0.93)

P

8.76e−10

2.79e−05

1.12e−13

0.8 1 1.2 1.4 1.6

OR

rs11771145

eStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.890.890.800.81

0.86

0.800.830.880.870.870.730.900.890.810.870.88

0.86

0.86

95% CI

(0.85−0.94)(0.82−0.98)(0.74−0.87)(0.74−0.89)

(0.84−0.89)

(0.61−1.03)(0.70−0.99)(0.73−1.07)(0.77−0.97)(0.60−1.26)(0.48−1.13)(0.79−1.03)(0.81−0.98)(0.72−0.92)(0.74−1.03)(0.76−1.01)

(0.82−0.90)

(0.84−0.89)

P

9.63e−17

4.47e−10

2.77e−25

0.6 0.8 1 1.2

OR

rs9331896 fStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.880.960.930.88

0.90

0.770.910.881.031.161.220.880.910.810.860.83

0.90

0.90

95% CI

(0.84−0.91)(0.88−1.04)(0.87−1.01)(0.81−0.97)

(0.87−0.93)

(0.59−0.99)(0.77−1.07)(0.71−1.08)(0.92−1.15)(0.80−1.70)(0.80−1.86)(0.77−1.00)(0.83−1.00)(0.71−0.92)(0.73−1.02)(0.72−0.96)

(0.86−0.94)

(0.87−0.92)

P

2.76e−11

4.48e−06

6.14e−16

0.6 0.8 1 1.2 1.4 1.6 1.8

OR

rs983392

16


Supplementary Figure 13Forest plots for (a) PICALM, (b) ABCA7 and (c) CD33

aStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.870.910.920.84

0.88

0.780.870.820.860.750.900.890.860.820.780.90

0.85

0.87

95% CI

(0.83−0.91)(0.83−0.99)(0.85−0.99)(0.77−0.92)

(0.85−0.91)

(0.60−1.02)(0.73−1.04)(0.68−0.99)(0.77−0.97)(0.51−1.11)(0.60−1.36)(0.78−1.01)(0.77−0.95)(0.73−0.94)(0.66−0.92)(0.78−1.05)

(0.81−0.89)

(0.85−0.89)

P

6.53e−16

1.10e−11

9.32e−26

0.6 0.8 1 1.2

OR

rs10792832

bStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.160.971.131.19

1.14

1.061.101.251.191.491.521.161.231.110.951.23

1.17

1.15

95% CI

(1.10−1.23)(0.82−1.15)(1.03−1.24)(1.04−1.36)

(1.10−1.20)

(0.76−1.47)(0.89−1.36)(0.94−1.68)(1.03−1.38)(0.93−2.40)(0.84−2.73)(0.98−1.37)(1.10−1.38)(0.94−1.31)(0.77−1.18)(1.02−1.48)

(1.10−1.24)

(1.11−1.19)

P

1.70e−09

9.92e−08

1.06e−15

0.8 1 1.2 1.4 1.6 1.8 2

OR

rs4147929

cStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.891.000.900.89

0.91

1.080.951.081.000.790.941.120.940.991.000.93

0.99

0.94

95% CI

(0.86−0.93)(0.92−1.10)(0.83−0.97)(0.77−1.02)

(0.88−0.94)

(0.82−1.42)(0.79−1.14)(0.89−1.30)(0.89−1.13)(0.52−1.20)(0.60−1.47)(0.97−1.30)(0.85−1.04)(0.87−1.12)(0.84−1.19)(0.80−1.09)

(0.94−1.04)

(0.91−0.96)

P

5.12e−08

6.89e−01

2.97e−06

0.6 0.8 1 1.2 1.4

OR

rs3865444

17


Supplementary Figure 14Forest plots for (a) HLA-DRB5/HAL-DRB1, (b) PTK2B, (c) SORL1, (d) SCL24A4 and (e) DSG2

a

Study

ADGCCHARGEEADIGERAD

Discovery

AustriaBelgiumGermanyGreeceHungaryItalySpainSwedenUKUSA

Replication

Combined

OR

1.101.101.111.17

1.11

1.191.061.131.500.781.011.061.321.161.04

1.12

1.11

95% CI

(1.05−1.16)(0.94−1.28)(1.01−1.22)(1.05−1.30)

(1.07−1.16)

(0.90−1.57)(0.88−1.29)(1.00−1.28)(0.99−2.29)(0.48−1.27)(0.86−1.18)(0.95−1.18)(1.16−1.52)(0.96−1.39)(0.88−1.22)

(1.06−1.18)

(1.08−1.15)

P

1.57e−08

4.23e−05

2.94e−12

0.6 0.8 1 1.2 1.4 1.6 1.8 2

OR

rs9271192 bStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.140.991.071.12

1.10

1.271.111.041.251.201.041.011.051.171.141.11

1.11

1.10

95% CI

(1.09−1.18)(0.91−1.08)(0.99−1.15)(1.02−1.23)

(1.07−1.14)

(0.98−1.66)(0.94−1.31)(0.87−1.26)(1.11−1.40)(0.80−1.80)(0.69−1.58)(0.89−1.15)(0.95−1.15)(1.03−1.32)(0.96−1.34)(0.96−1.28)

(1.06−1.17)

(1.08−1.13)

P

3.27e−09

4.32e−06

7.37e−14

0.8 1 1.2 1.4 1.6 1.8

OR

rs28834970

cStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.750.850.800.66

0.76

1.250.560.820.891.071.380.920.660.671.010.67

0.78

0.77

95% CI

(0.67−0.83)(0.69−1.05)(0.66−0.97)(0.52−0.86)

(0.70−0.83)

(0.64−2.43)(0.38−0.85)(0.43−1.55)(0.67−1.16)(0.48−2.40)(0.34−5.55)(0.68−1.23)(0.51−0.85)(0.47−0.95)(0.66−1.57)(0.45−0.98)

(0.70−0.88)

(0.72−0.82)

P

4.98e−11

4.00e−05

9.73e−15

0.5 1 1.5 2

OR

rs11218343 dStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.900.890.930.86

0.90

1.000.990.770.900.860.830.860.871.051.030.95

0.93

0.91

95% CI

(0.85−0.95)(0.80−0.99)(0.86−1.02)(0.75−0.98)

(0.87−0.94)

(0.74−1.36)(0.82−1.21)(0.60−0.99)(0.79−1.03)(0.54−1.40)(0.53−1.31)(0.73−1.02)(0.77−0.98)(0.91−1.22)(0.85−1.25)(0.81−1.13)

(0.88−0.98)

(0.88−0.94)

P

1.47e−07

7.79e−03

5.54e−09

0.6 0.8 1 1.2

OR

rs10498633

eStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.480.490.600.71

0.54

0.871.080.760.892.098.130.751.200.311.331.24

1.01

0.73

95% CI

(0.36−0.64)(0.05−5.05)(0.36−0.97)(0.44−1.16)

(0.43−0.67)

(0.25−3.03)(0.49−2.36)(0.28−2.11)(0.49−1.60)

(0.32−13.87)(0.91−72.69)(0.42−1.35)(0.74−1.95)(0.09−1.05)(0.61−2.90)(0.66−2.33)

(0.80−1.28)

(0.62−0.86)

P

4.63e−08

9.04e−01

1.05e−04

0.5 1 1.5 2

OR

rs8093731

18


Supplementary Figure 15Forest plots for (a) INPP5D, (b) MEF2C, (c) NME8, (d) ZCWPW1, (e) CELF1 and (f) FERMT2

aStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.061.101.091.07

1.07

0.821.131.071.160.731.191.031.081.111.231.17

1.10

1.08

95% CI

(1.01−1.10)(1.01−1.20)(1.01−1.18)(0.97−1.17)

(1.03−1.10)

(0.64−1.04)(0.95−1.33)(0.89−1.29)(1.04−1.30)(0.50−1.05)(0.78−1.82)(0.90−1.17)(0.98−1.19)(0.98−1.25)(1.04−1.44)(1.01−1.35)

(1.05−1.15)

(1.05−1.11)

P

9.58e−05

5.66e−05

3.17e−08

0.6 0.8 1 1.2 1.4 1.6 1.8

OR

rs35349669 bStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.900.980.940.96

0.92

1.020.981.080.991.100.810.960.920.850.880.87

0.93

0.93

95% CI

(0.86−0.94)(0.89−1.08)(0.87−1.01)(0.87−1.05)

(0.89−0.95)

(0.78−1.32)(0.83−1.16)(0.87−1.32)(0.88−1.11)(0.77−1.57)(0.55−1.20)(0.84−1.09)(0.84−1.02)(0.75−0.96)(0.75−1.03)(0.75−1.01)

(0.89−0.98)

(0.90−0.95)

P

2.55e−06

3.38e−03

3.23e−08

0.6 0.8 1 1.2 1.4

OR

rs190982

cStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.920.930.970.95

0.93

0.780.980.990.880.920.740.950.940.900.880.86

0.91

0.93

95% CI

(0.88−0.96)(0.85−1.01)(0.90−1.04)(0.87−1.04)

(0.90−0.96)

(0.60−1.01)(0.83−1.16)(0.81−1.23)(0.78−0.98)(0.63−1.33)(0.48−1.13)(0.83−1.09)(0.86−1.03)(0.79−1.02)(0.74−1.04)(0.74−0.99)

(0.87−0.95)

(0.90−0.95)

P

1.31e−05

6.27e−05

4.76e−09

0.6 0.8 1 1.2

OR

rs2718058 dStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.911.030.950.88

0.92

1.100.810.860.860.821.050.960.930.900.850.84

0.89

0.91

95% CI

(0.87−0.95)(0.94−1.14)(0.88−1.03)(0.80−0.97)

(0.89−0.96)

(0.84−1.44)(0.68−0.97)(0.70−1.07)(0.76−0.97)(0.56−1.22)(0.66−1.67)(0.83−1.11)(0.84−1.04)(0.78−1.03)(0.71−1.01)(0.72−0.98)

(0.85−0.94)

(0.89−0.94)

P

7.40e−06

9.69e−06

5.58e−10

0.6 0.8 1 1.2 1.4 1.6

OR

rs1476679

eStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.051.091.141.12

1.08

1.061.021.291.141.171.181.111.080.981.031.17

1.09

1.08

95% CI

(1.01−1.10)(1.00−1.19)(1.05−1.23)(1.01−1.23)

(1.04−1.11)

(0.82−1.38)(0.86−1.21)(1.03−1.61)(1.02−1.29)(0.80−1.71)(0.79−1.77)(0.97−1.27)(0.97−1.19)(0.85−1.12)(0.87−1.23)(1.00−1.38)

(1.04−1.14)

(1.05−1.11)

P

6.73e−06

4.07e−04

1.12e−08

0.8 1 1.2 1.4 1.6

OR

rs10838725 fStudy

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

1.141.081.171.10

1.13

1.281.091.080.951.100.841.171.361.151.461.25

1.17

1.14

95% CI

(1.06−1.23)(0.94−1.24)(1.02−1.33)(0.95−1.28)

(1.07−1.19)

(0.82−1.97)(0.82−1.45)(0.81−1.44)(0.78−1.14)(0.48−2.51)(0.41−1.72)(0.90−1.52)(1.12−1.65)(0.95−1.41)(1.11−1.92)(0.97−1.62)

(1.08−1.26)

(1.09−1.19)

P

1.01e−05

1.64e−04

7.94e−09

0.5 1 1.5 2

OR

rs17125944

19


Supplementary Figure 16Forest plot for CASS4

Study

ADGCCHARGEEADIGERAD

Discovery


Replication

Combined

OR

0.860.810.890.95

0.87

1.030.910.950.940.920.610.940.830.720.920.99

0.89

0.88

95% CI

(0.80−0.93)(0.69−0.96)(0.78−1.02)(0.80−1.13)

(0.82−0.92)

(0.64−1.65)(0.68−1.22)(0.57−1.58)(0.77−1.14)(0.50−1.67)(0.31−1.19)(0.77−1.15)(0.71−0.98)(0.55−0.94)(0.68−1.24)(0.76−1.29)

(0.82−0.96)

(0.84−0.92)

P

1.62e−06

4.07e−03

2.46e−08

0.4 0.6 0.8 1 1.2 1.4 1.6

OR

rs7274581

20


Supplementary Figure 17Regional association of the PTK2B/CLU SNPs with AD risk (a) before and (b) after conditional analyses

(adjustment for the best CLU signal (rs9331896))

a

0

2

4

6

8

10

0

20

40

60

80

100

Recom

bination rate (cM/M

b)

rs9331896

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0.4

0.6

0.8

r2

STMN4

TRIM35

PTK2B

CHRNA2

EPHX2 CLU

SCARA3

CCDC25

ESCO2

PBK SCARA5

MIR4287


b

0

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4

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8

10

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40

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Recom

bination rate (cM/M

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0.2

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0.8

r2

STMN4

TRIM35

PTK2B

CHRNA2

EPHX2 CLU

SCARA3

CCDC25

ESCO2

PBK SCARA5

MIR4287


21


Supplementary Figure 18Evaluation of genotyping biases by the comparison of the minor allele frequency (MAF) observed

in stage 2 control samples and the 1000 genome data set (European ancestry individuals)

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−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15

01

23

45

6

Frequency difference

−log

10(p

valu

e)

●

●● ●● ● ●●●● ●● ●●● ●●●●● ●●●● ● ● ●● ● ●●●● ●●● ●● ●● ●● ●● ● ●●● ● ●● ●●●●●● ●●●● ● ● ● ●●●●●● ●● ●

●

● ●● ● ● ● ●●●

●

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●

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●●

●

●

●

●●●●

●

●

●

●●●

●

●●

●

●●●

●

●●

●

●

●●●

●●

●●

●

●●●●●

●

●

●●●●●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●●

●

●

●●●●●●

●

●●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●

●

●

●

●

●

●

●

●

MAF < 0.001MAF [0.001,0.01[MAF [0.01,0.05[MAF [0.05,0.1[MAF [0.1,0.2[MAF >= 0.2

22


Supplementary Table 1Full description of the different datasets from each consortium

Consortium AD cases Controls

N % women Mean AAO (SD) N % women Mean AAE (SD)ADGC

ACT 566 63.1 83.9 (4.8) 1,696 55.8 81.1 (6.0)ADC1 1,411 53.9 72.5 (7.1) 515 59.2 75.0 (8.0)ADC2 737 51.0 73.2 (7.1) 160 68.8 75.7 (7.9)ADC3 364 50.8 74.4 (8.0) 570 63.9 75.2 (9.8 )ADNI 268 42.2 73.0 (7.2) 173 40.5 78.6 (5.5)GSK 669 56.8 74.6 (6.2) 713 64.0 73.8 (7.0)LOAD 1,811 64.9 73.6 (6.7) 1,572 60.2 74.0 (8.5)MAYO 728 57.6 - 1,173 51.2 72.9 (4.3)MIRAGE 509 63.7 71.2 (6.5) 742 58.1 72.0 (7.2)OHSU 131 61.8 86.1 (5.5) 153 54.9 83.9 (7.6)ROSMAP 291 70.5 85.6 (6.3) 776 72.0 82.0 (7.0)TGEN2 129 46.6 74.9 (7.2) 493 37.7 80.1 (8.7)UMVUMSS 1,070 63.7 73.9 (7.8) 1,128 61.3 73.0 (7.1)UPITT 1,271 63.1 72.9 (6.4) 841 63.4 75.4 (6.1)WASHU 318 55.7 74.2 (8.0) 187 60.4 76.9 (8.4)

CHARGEAGES 78 50.0 81.0 (5.0) 2,694 58.0 76.0 (5.0)CHS.inc 353 68.9 82.1 (5.1) 1,732 62.0 74.5 (4.5)CHS.prev 68 50.0 80.1 (5.7) 102 61.5 74.8 (4.7)FHS.inc 117 59.0 86.4 (6.4) 2,966 54.1 75.9 (9.3)FHS.prev 66 72.8 85.0 (8.0) 3,334 45.2 70.1 (10.0)RS.inc 462 59.0 82.0 (7.0) 5,238 59.0 69.0 (9.0)RS.prev 171 75.0 84.0 (9.0) 5,700 59.0 69.0 (9.0)

EADI 2,243 64.9 68.5 (8.9) 6,017 60.7 74.0 (5.4)

GERAD 3,177 64.0 73.0 (8.5) 7,277 51.8 51.0 (11.8)

23


Supplementary Table 2General description of the imputation and meta-analysis processes and number of SNPs available after each step

Study Imputation Number of SNPs used Number of SNPs GWAs softwareSoftware for imputation imputedACT IMPUTE2 536,993 11,577,537 PLINKADC1 IMPUTE2 534,380 11,583,487 PLINKADC2 IMPUTE2 527,149 11,317,286 PLINKADC3 IMPUTE2 661,363 11,599,854 PLINKADNI IMPUTE2 548,414 11,578,603 PLINKAGES Mach/Minimac 313,430 11,572,501 probABELCHS.inc Mach/Minimac 313,933 11,863,202 probABELCHS.prev Mach/Minimac 313,933 11,863,202 probABELEADI Mach/Minimac 492,893 11,827,280 probABELFHS.inc Mach/Minimac 412,053 11,497,776 probABELFHS.prev Mach/Minimac 412,053 11,497,776 probABELGERAD IMPUTE2 419,064 11,572,662 SNPtestGSK IMPUTE2 442,833 11,464,979 PLINKLOAD IMPUTE2 331,230 10,945,471 R (GEE)MAYO IMPUTE2 309,603 11,548,046 PLINKMIRAGE IMPUTE2 562,414 11,282,782 R (GEE)OHSU IMPUTE2 558,930 11,577,732 PLINKROSMAP IMPUTE2 635,774 11,573,349 PLINKRS.inc Mach/Minimac 483,099 11,281,682 probABELRS.prev Mach/Minimac 483,099 11,281,682 probABELTGEN2 IMPUTE2 658,617 11,573,262 PLINKUMVUMSS IMPUTE2 1,477,026 10,952,949 PLINKUPITT IMPUTE2 738,049 11,326,852 PLINK

Study Number of SNPs Final number of SNPs Number of PCs for Genomic inflationremoved1 analysed adjustment factor (I)

ACT 4,258,880 7,318,657 3 0.998ADC1 4,340,043 7,243,444 3 1.014ADC2 4,172,978 7,144,308 3 1.017ADC3 4,233,793 7,366,061 3 1.011ADNI 4,332,367 7,246,236 2 1.017AGES 5,059,184 6,513,317 2 1.033CHS.inc 5,292,129 6,571,073 2 1.103CHS.prev 5,332,436 6,530,766 2 1.036EADI 4,980,623 6,846,657 8 1.045FHS.inc 5,130,630 6,367,146 2 1.009FHS.prev 5,245,202 6,252,574 2 0.996GERAD 4,565,639 7,007,023 3 1.087GSK 4,629,104 6,835,875 2 1.004LOAD 3,502,275 7,443,196 2 1.022MAYO 4,432,121 7,115,925 4 1.018MIRAGE 4,155,565 7,127,217 3 1.028OHSU 4,466,010 7,111,722 2 1.036ROSMAP 4,428,005 7,145,344 2 1.012RS.inc 4,644,745 6,636,937 2 1.045RS.prev 4,647,095 6,634,587 2 1.057TGEN2 4,432,460 7,140,802 3 1.024UMVUMSS 4,424,246 6,528,703 4 1.020UPITT 4,096,429 7,230,423 3 1.011WASHU 4,292,076 7,289,958 2 1.022

1 filter : MAF < 0.01, R2 or Info <0 .3, |β| > 5, SE ≤ 0, P = 0 or 1

24


Supplementary Table 3Summary of eQTL annotation for the loci reaching genome-wide significance in the combined stage 1 and stage 2

Top

SNP1

Chr

.Po

sitio

nC

lose

stG

ene2

Nb

ofSi

gnifi

cant

SNPs

3Q

TL

Gen

eQ

TL

Type

Nb

ofre

port

edQ

TL

SNPs

3,4

Bes

tQT

LSN

P

SNP

rsID

Posi

tion

P-va

lue

Act

inC

is/T

rans

Ref

eren

ce5

rs67

3383

92

127,

892,

810

BIN

176

BIN

1eQ

TL

5rs

1020

0967

127,

841,

769

2.24

x10−

35ci

s53

rs92

7119

26

32,5

78,5

30H

LA-D

RB

5/H

LA-D

RB

120

1AO

AH

eQT

L1

rs39

5714

632

,681

,530

6.57

x10−

30tr

ans

54F

LJ20

186

eQT

L1

rs39

5714

632

,681

,530

2.23

x10−

29tr

ans

54H

LA-D

QA

1eQ

TL

1rs

3957

146

32,6

81,5

309.

72x1

0−53

cis

54H

LA-D

QA

1ex

on-Q

TL

7rs

6927

022

32,6

12,3

972.

96x1

0−14

cis

55H

LA-D

QA

1tr

ansc

ript

-QT

L2

rs69

2702

232

,612

,397

7.42

x10−

11ci

s55

HLA

-DQ

A2

eQT

L9

rs39

5714

632

,681

,530

1.06

x10−

10ci

s56

HLA

-DQ

A2

tran

scri

pt-Q

TL

1rs

6927

022

32,6

12,3

971.

58x1

0−05

cis

55H

LA-D

QB

1eQ

TL

14rs

9272

545

32,6

06,8

851.

07x1

0−58

cis

53H

LA-D

QB

1ex

on-Q

TL

7rs

6927

022

32,6

12,3

971.

29x1

0−14

cis

55H

LA-D

QB

1tr

ansc

ript

-QT

L4

rs69

2702

232

,612

,397

8.08

x10−

14ci

s55

HLA

-DR

Atr

ansc

ript

-QT

L1

rs69

2702

232

,612

,397

2.03

x10−

05ci

s55

HLA

-DR

B1

eQT

L51

rs23

9516

632

,388

,275

2.57

x10−

190

cis

54H

LA-D

RB

1ex

on-Q

TL

8rs

3135

344

32,3

95,0

362.

59x1

0−10

cis

55H

LA-D

RB

1tr

ansc

ript

-QT

L2

rs69

2702

232

,612

,397

9.09

x10−

08ci

s55

HLA

-DR

B4

eQT

L12

rs27

6098

032

,565

,201

4.03

x10−

51ci

s53

HLA

-DR

B5

eQT

L45

rs23

9516

632

,388

,275

3.73

x10−

77ci

s54

HLA

-DR

B5

exon

-QT

L1

rs31

3534

432

,395

,036

3.89

x10−

05ci

s55

HLA

-DR

B6

eQT

L2

rs39

5714

632

,681

,530

8.62

x10−

31ci

s54

LIM

S1eQ

TL

1rs

2395

166

32,3

88,2

753.

64x1

0−36

tran

s54

PSM

B9

eQT

L1

rs23

9516

632

,388

,275

1.05

x10−

16ci

s54

SSR

P1

eQT

L1

rs39

5714

632

,681

,530

2.47

x10−

12tr

ans

54

rs14

7667

97

100,

004,

446

ZCW

PW

16

GAT

SeQ

TL

1rs

1476

679

100,

004,

446

4.45

x10−

21ci

s54

PIL

RB

eQT

L1

rs14

7667

910

0,00

4,44

69.

06x1

0−20

cis

54TR

IM4

eQT

L1

rs14

7667

910

0,00

4,44

61.

37x1

0−17

cis

54

rs28

8349

708

27,1

95,1

21P

TK2B

35D

PYS

L2ex

on-Q

TL

1rs

1705

7043

27,2

20,3

106.

46x1

0−05

cis

55P

TK2B

eQT

L2

rs17

0570

4327

,220

,310

2.13

x10−

20ci

s54

rs93

3189

68

27,4

67,6

86C

LU35

DP

YSL2

exon

-QT

L1

rs17

0570

4327

,220

,310

6.46

x10−

05ci

s55

PTK

2BeQ

TL

2rs

1705

7043

27,2

20,3

102.

13x1

0−20

cis

54

rs10

8387

2511

47,5

57,8

71C

ELF

112

C1Q

TNF

4eQ

TL

6rs

7933

019

47,5

09,1

371.

08x1

0−10

cis

57M

YBP

C3

eQT

L2

rs12

2929

1147

,449

,072

1.72

x10−

25ci

s54

SPI1

eQT

L2

rs15

3457

647

,419

,663

1.42

x10−

21ci

s54

rs98

3392

1159

,923

,508

MS4

A6A

135

MS4

A4A

eQT

L18

rs10

2625

560

,029

,949

4.53

x10−

18ci

s54

1A

repr

esen

ted

the

SNPs

show

ing

the

best

leve

lofa

ssoc

iatio

naf

term

eta-

anal

ysis

ofth

est

age

1an

dst

age

22±

100k

b3±

500k

b4

Fort

hatQ

TL

gene

and

that

QT

Lty

pe5

Ref

eren

ces

are

inth

esu

pple

men

tary

note

25


Supplementary Table 4Summary of stage 1, stage 2 and overall meta-analyses for SNPs showing suggestive association

with AD risk after stage 1 and stage 2

SNP1

Chr

.Po

sitio

n2C

lose

stge

ne3

Maj

or/M

inor

alle

les

MA

F4St

age

1St

age

2O

vera

ll

OR

5(9

5%C

I)M

eta

P-va

lue

OR

5(9

5%C

I)M

eta

P-va

lue

OR

5(9

5%C

I)M

eta

Pva

lue

I2(%

),P-

valu

e6

rs66

7827

51

193,

625,

233

–G

/C0.

169

1.10

(1.0

6-1.

15)

3.9x

10−

61.

07(1

.01-

1.13

)2.

2x10−

21.

09(1

.05-

1.13

)3.

4x10−

727

,7.2

x10−

2

rs64

4879

94

11,6

30,0

49H

S3ST

1C

/T0.

300

1.08

(1.0

4-1.

12)

9.3x

10−

61.

08(1

.03-

1.13

)2.

0x10−

31.

08(1

.05-

1.11

)6.

6x10−

80,

6.4x

10−

1

rs72

8073

435

179,

238,

261

SQST

M1

C/T

0.01

61.

35(1

.15-

1.58

)2.

1x10−

41.

35(1

.13-

1.62

)1.

1x10−

31.

35(1

.20-

1.52

)7.

4x10−

70,

5.1x

10−

1

rs93

8104

06

41,1

54,6

50TR

EM

L2C

/T0.

297

0.94

(0.9

1-0.

98)

6.0x

10−

40.

91(0

.87-

0.95

)1.

4x10−

40.

93(0

.91-

0.96

)6.

3x10−

70,

8.9x

10−

1

rs78

1838

28

96,0

54,0

00N

DU

FAF

6C

/T0.

469

1.07

(1.0

4-1.

10)

1.6x

10−

51.

07(1

.03-

1.12

)1.

4x10−

31.

07(1

.04-

1.10

)8.

0x10−

80,

9.3x

10−

1

rs79

2072

110

11,7

20,3

08E

CH

DC

3A

/G0.

387

1.07

(1.0

4-1.

11)

1.6x

10−

51.

07(1

.02-

1.12

)5.

3x10−

31.

07(1

.04-

1.10

)2.

9x10−

70,

6.7x

10−

1

rs10

7516

6711

941,

941

AP

2A2

T/A

0.36

60.

93(0

.90-

0.96

)1.

8x10−

50.

94(0

.90-

0.99

)1.

0x10−

20.

93(0

.91-

0.96

)6.

3x10−

719

,1.6

x10−

1

rs72

9524

612

43,9

67,6

77A

DA

MTS

20T

/G0.

406

1.07

(1.0

3-1.

10)

1.0x

10−

41.

08(1

.03-

1.13

)7.

2x10−

41.

07(1

.04-

1.10

)3.

0x10−

70,

4.9x

10−

1

rs23

3740

614

107,

180,

574

IGH

@C

/T0.

103

0.86

(0.8

0-0.

92)

3.2x

10−

50.

89(0

.83-

0.96

)1.

9x10−

30.

87(0

.83-

0.92

)2.

7x10−

70,

6.8x

10−

1

rs80

3545

215

51,0

40,7

98SP

PL2

AT

/C0.

339

0.94

(0.9

1-0.

97)

3.8x

10−

40.

91(0

.87-

0.96

)1.

2x10−

40.

93(0

.91-

0.96

)3.

2x10−

721

,1.3

x10−

1

rs74

6151

6615

64,7

25,4

90TR

IP4

T/C

0.02

01.

40(1

.22-

1.61

)2.

0x10−

61.

18(1

.03-

1.36

)1.

7x10−

21.

29(1

.17-

1.42

)4.

3x10−

70,

6.5x

10−

1

rs72

2515

117

5,13

7,04

7SC

IMP

G/A

0.12

11.

11(1

.06-

1.17

)5.

7x10−

61.

08(1

.01-

1.16

)1.

7x10−

21.

10(1

.06-

1.15

)3.

7x10−

715

,2.2

x10−

1

chr1

7:61

5381

4817

61,5

38,1

48AC

EG

/A0.

018

1.29

(1.1

2-1.

49)

5.7x

10−

41.

42(1

.19-

1.70

)1.

1x10−

41.

34(1

.20-

1.50

)3.

1x10−

70,

8.8x

10−

1

1A

repr

esen

ted

the

SNPs

show

ing

the

best

leve

lofa

ssoc

iatio

naf

term

eta-

anal

ysis

ofth

est

age

1an

dst

age

22±

Bui

ld37

,Ass

embl

yH

g19

3±

100k

b4

Ave

rage

inSt

age

1sa

mpl

e5

Cal

cula

ted

with

resp

ectt

oth

em

inor

alle

le6

Coc

hran

’sQ

test

26


Supplementary Table 5Conditional analysis of the two best associated CLU and PTK2B SNPs in stage 2

Gene SNP Separate analysis Conditional analysis

OR [95% CI] Meta Pvalue OR [95% CI] Meta Pvalue

CLU rs9331896 0.87 [0.83-0.91] 5.9x10−8 0.87 [0.83-0.91] 1.1x10−8

PTK2B rs28834970 1.09 [1.04-1.15] 9.6x10−4 1.09 [1.04-1.14] 6.5x10−4

27


Supplementary Table 6Description of the population attributable/preventive fractions for the GWAS-defined genes in stage 2

SNP Gene MAF in controls PAF(%) PAF Typers4147929 ABCA7 0.162 2.8 riske4 APOE 0.123 27.3 riskrs6733839 BIN1 0.366 8.1 riskrs7274581 CASS4 0.088 1.1 preventivers10948363 CD2AP 0.255 2.3 riskrs10838725 CELF1 0.312 2.4 riskrs9331896 CLU 0.398 5.3 preventivers6656401 CR1 0.191 3.7 riskrs11771145 EPHA1 0.350 3.1 preventivers17125944 FERMT2 0.079 1.5 riskrs9271192 HLA 0.277 3.2 riskrs35349669 INPP5D 0.462 4.6 riskrs190982 MEF2C 0.389 2.7 preventivers983392 MS4A6A 0.406 4.2 preventivers2718058 NME8 0.368 2.9 preventivers10792832 PICALM 0.365 5.3 preventivers28834970 PTK2B 0.358 3.1 riskrs10498633 SLC24A4/RIN3 0.212 1.5 preventivers11218343 SORL1 0.044 1.1 preventivers1476679 ZCWPW1 0.293 3.2 preventive

28


Supplementary Table 7Full description of the GERAD stage 1 datasets

AD cases Controls

N % women Mean AAO (SD) N % women Mean AAE (SD)GERAD

MRC 1008 70.3 80.9 (6.5) 873 61.6 75.9 (6.3)ARUK 939 61.0 76.6 (9.6) 82 59.8 77.9 (7.6)BONN 551 63.7 72.9 (8.3) 37 64.9 79.5 (3.6)WASHU 423 56.0 82.1 (9.0) 156 65.4 78.5 (9.7)NIMH 127 63.0 80.1 (6.1) - - -UCL:PRION 82 59.8 63.6 (9.9) - - -UCL:LASER 47 74.5 80.6 (7.9) - - -1958BC - - - 5342 49.8 45.0 (0.0)KORA - - - 434 49.1 56.0 (7.2)HNR - - - 353 52.9 54.6 (5.3)MAYO1 728 57.6 - 1173 51.2 72.9 (4.3)

1 MAYO study is part of both ADGC and GERAD consortia, for the purposes of the mega-meta analysis, MAYO was removed from the GERAD

dataset and included in the ADGC dataset only

29


Supplementary Table 8Full description of the stage 2 datasets by centre

Country Centre Consortium AD cases Controls

N % women Mean age (SD) Mean AAO (SD) N % women Mean AAE (SD)Austria Graz CHARGE 210 61.0 75.4 (7.9) 72.5 (8.1) 829 43.3 65.6 (8.0)

Belgium Antwerp EADI 878 66.1 78.8 (8.2) 75.4 (8.5) 661 59.5 65.7 (14.3)Finland Kuopio EADI 422 68.0 71.4 (6.9) 71.4 (6.9) 562 59.3 69.1 (6.2)

Germany Bonn 1 GERAD 530 61.7 73.3 (8.6) 73.3 (8.6) 1,096 52.4 64.8 (10.9)Germany Bonn 2 GERAD 7 57.1 76.0 (8.7) 70.0 (3.9) 490 67.6 79.6 (3.2)Germany Essen GERAD 150 65.3 81.5 (6.6) 76.0 (6.9) 262 60.3 76.2 (6.0)Germany Munich GERAD 285 67.4 73.4 (8.7) 70.7 (8.7) 530 37.7 66.6 (3.4)Greece Thessaloniki GERAD 256 63.3 73.1 (7.9) 69.2 (8.0) 229 34.1 49.3 (16.4)

Hungary Budapest ADGC 125 68.0 78.9 (7.3) 74.9 (6.8) 100 69.0 74.4 (6.5)Italy Cagliari EADI 130 73.1 77.3 (6.8) 74.9 (6.5) 110 55.5 65.7 (7.8)Italy Florence EADI 441 60.1 70.7 (8.4) 67.1 (8.5) 77 54.5 64.0 (13.1)Italy Milan EADI 314 67.5 78.1 (7.6) 73.3 (7.5 ) 165 60.6 69.8 (11.1)Italy Perugia EADI 124 73.4 78.8 (6.8) - 79 51.9 74.4 (6.2)Italy Pisa EADI 27 77.8 74.1 (8.7) 72.1 (8.7) 10 70.0 52.6 (22.2)Italy Rome EADI 388 70.9 75.7 (7.5) 73.1 (7.8) 42 61.9 68.6 (6.5)Italy San Giovanni Rotonda EADI 139 64.7 78.8 (6.9) 78.5 (7.4) 80 33.8 76.3 (7.0)Italy Troina EADI 166 60.8 77.6 (8.0) 71.7 (8.3) 157 61.8 72.1 (8.3)Spain Barcelona 1 CHARGE 475 73.7 80.2 (6.7) 78.9 (6.7) 478 64.6 63.3 (9.4)Spain Barcelona 2 EADI 280 71.4 77.1 (5.4) 77.1 (5.4) 200 20.0 75.5 (5.2)Spain Las Palmas de Gran Canaria EADI 255 68.2 80.9 (6.8) 75.8 (7.0) 294 36.4 70.1 (5.9)Spain Madrid EADI 92 60.9 70.1 (9.6) 68.4 (9.9) 153 61.4 67.7 (14.4)Spain Oviedo EADI 242 62.8 81.1 (7.1) 78.1 (6.8) 169 66.3 73.3 (8.2)Spain Pamplone GERAD 421 59.4 74.9 (9.2) 69.2 (9.2) 338 59.8 67.1 (10.9)Spain Santander EADI 356 63.2 76.6 (6.9) 73.7 (7.0) 289 68.5 80.9 (7.5)

Sweden Stockholm EADI 514 61.3 69.6 (9.3) 87.0 (5.6 ) 1,272 62.8 69.8 (8.9)Sweden Uppsala EADI 283 62.5 76.5 (8.0) 76.5 (8.0) 234 62.8 74.8 (6.3)

UK Belfast GERAD 178 68.5 76.8 (7.3) 72.7 (6.6) 186 69.9 74.1 (9.0)UK Bristol GERAD 12 58.3 82.1 (9.6) 69.4 (10.7) 7 42.9 78.6 (8.4)UK Caerphilly GERAD 30 0.0 74.3 (4.1) - 519 0.0 72.1 (4.0)UK Southampton GERAD 107 66.4 83.8 (7.3) 78.6 (7.8) 79 55.7 74.0 (7.9)UK Nottingham GERAD 163 50.3 76.3 (9.4) 72.9 (8.7) 275 48.7 76.7 (6.7)

USA Jacksonville GERAD 572 61.9 83.5 (7.6) 83.5 (7.6) 1,340 54.0 79.3 (6.8)

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Supplementary Table 9Test of missingness difference between cases and controls across the stage 2 samples

SNP Austria Belgium Finland Germany Germany Greece Hungary Italy Spain Sweden UK USA(imputed)

Sign

ifica

nthi

ts

rs6656401 1 1 1 1 1 1 1 3.2x10−1 1 5.5x10−1 1 3.0x10−1

rs6733839 1 1 1 1 1 1 1 1 1 1 1 1rs35349669 1 4.3x10−1 1 1 1 1 1 1 1 1 1 1rs190982 1 1 1 1 1 5.0x10−1 1 1 1 1 1 1rs9271192 1.7x10−5 9.3x10−6 6.7x10−1 3.0x10−2 1 4.5x10−1 1.5x10−1 7.0x10−1 2.4x10−1 5.0x10−6 2.9x10−1 6.0x10−3

rs10948363 1 1 1 1 1 1 1 5.6x10−1 6.7x10−1 1 1 1rs2718058 1 1 1 1 1 1 1 1 1 1 1 1rs1476679 1 1 1 1 1 1 1 1 1 1 1 1rs11771145 1 1 1 1 1 1 1 1 4.7x10−1 1 1 1rs28834970 2.1x10−1 1 1 1 1 1 1 1 1 1 1 1rs9331896 1 1 1 1 1 1 1 1 1 1 1 1rs10838725 9.2x10−3 4.3x10−1 4.8x10−1 4.4x10−1 1 1 1 9.6x10−2 2.0x10−3 1 4.3x10−1 4.4x10−1

rs983392 1 1 1 1 1 1 1 1 4.7x10−1 3.5x10−1 1 1rs10792832 1 1 1 1 1 5.0x10−1 1 1 1 1 1 1rs11218343 1 1 1 1 1 1 1 1 1 1 1 1rs17125944 1 1 1 1 1 1 1 1 1 1 1 1rs10498633 1 1 1 1 1 1 1 3.0x10−1 4.7x10−1 1 1 1rs4147929 2.1x10−1 1 1 2.6x10−1 1 1 1 3.0x10−1 1 1 1 1rs7274581 1 1 1 6.6x10−1 1 1 1 1 1 1 1 1

Sugg

estiv

ehi

ts

rs6678275 1 1 1 1 1 1 1 1 1 1 1 1rs6448799 1 1 1 1 1 1 1 1 1 3.5x10−1 1 1rs72807343 2.1x10−1 1.8x10−1 2.6x120−1 6.9x10−1 1 1 1 1 8.2x10−2 1 1.8x10−1 3.2x10−1

rs9381040 1 1 1 1 1 1 1 1 1 1 1 1rs7818382 1 1 1 4.6x10−1 1 1 1 1 1 1 1 1rs7920721 1 1 1 1 1 1 1 1 4.7x10−1 1 1 1rs10751667 1.7x10−5 2.5x10−1 8.3x10−1 1.2x10−5 1 7.2x10−1 7.7x10−1 2.5x10−1 7.8x10−1 8.8x10−1 6.9x10−1 3.8x10−1

rs7295246 1 1 1 1 1 1 1 1 1 1 1 1rs2337406 1.9x10−12 3.2x10−6 4.9x10−5 5.4x10−1 1 1 7.8x10−1 9.3x10−2 1.2x10−2 2.8x10−1 2.5x10−3 2.9x10−7

rs8035452 1 1 1 1 1 1 1 1 1 1 1 1rs74615166 1 1 1 1 1 1 1 1 1 1 1 1rs7225151 4.4x10−2 1 1 1 1 5.0x10−1 1 1 1 1 1 117:61538148 1 1 1 1 1 1 1 1 1 1 1 1

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Supplementary Table 10Description of the stage 2 samples before and after quality control according to the country of origin

Austria Belgium Finland Germany Germany Greece Hungary(imputed)Initial sample size 1,149 1,638 1,119 1,862 1,790 564 299

Gender 18 28 5 43 0 17 2Missingness 33 19 103 75 31 5 4Heterozygosity 1 0 0 0 0 0 0Duplicates 11 18 4 10 3 23 40Relatedness 8 21 24 3 8 9 43Ancestry 30 4 0 0 12 0 0Missing phenotype 9 12 10 17 0 19 1Plate 0 0 0 0 0 0 0Controls with age < 25 0 0 0 0 0 17 0Part of stage 1 0 0 0 0 110 0 0Excluded (n) 110 99 135 138 164 79 74Excluded (%) 9.6 6.0 12.1 7.4 9.0 14.0 24.7

Final sample size 1,039 1,539 984 1,724 1,626 485 255Cases 210 878 422 442 530 256 125Controls 829 661 562 1,282 1,096 229 100

Italy Spain Sweden UK USA TOTAL

Initial sample size 2,926 4,393 2,368 2,435 2,135 22,618Gender 127 85 20 69 17 431Missingness 32 72 8 55 16 453Heterozygosity 0 0 0 0 0 1Duplicates 105 76 5 30 14 339Relatedness 33 74 11 87 66 387Ancestry 3 9 6 4 16 84Missing phenotype 153 48 17 706 106 1,098Plate 91 0 0 0 0 91Controls with age < 25 1 3 0 0 0 21Part of stage 1 0 0 0 18 0 128Excluded (n) 477 351 65 879 223 2,794Excluded (%) 16.3 8.0 2.7 36.1 10.4 12.3

Final sample size 2,449 4,042 2,303 1,556 1,912 19,884Cases 1,729 2,121 797 490 572 8,572Controls 720 1,921 1,506 1,066 1,340 11,312

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Supplementary Note

Full I-GAP datasets description

Written informed consent was obtained from study participants or, for those with substantial cognitive impair-ment, from a caregiver, legal guardian, or other proxy, and the study protocols for all populations were reviewedand approved by the appropriate Institutional review boards.

Alzheimer’s Disease Genetics Consortium (ADGC)

The ADGC dataset comprises subjects from the Adult Changes in Thought (ACT)/ Electronic Medical Recordsand Genetics (eMERGE) study, the National Institute on Aging (NIA) Alzheimer Disease Centers (ADCs), theAlzheimer Disease Neuroimaging Initiative (ADNI) Study, the Multi-Site Collaborative Study for Genotype-Phe-notype Associations in Alzheimers Disease (GenADA) Study, the University of Miami/Vanderbilt University/Mt.Sinai School of Medicine (UM/VU/MSSM), the MIRAGE Study, Oregon Health and Science University (OHSU),the NCRAD/NIA-LOAD Study, the Translational Genomics Research Institute series 2 (TGEN2) dataset, subjectsfrom the Mayo Clinic, the Rush University Religious Orders Study/Memory and Aging Project (ROSMAP), theUniversity of Pittsburgh (UP), and Washington University (WU). Detailed descriptions of the ascertainment andevaluation of subjects in the ADC, ADNI, UM/VU/MSSM, MIRAGE, and NCRAD/NIA-LOAD cohorts have beenprovided elsewhere [1]; brief descriptions included here note any differences between data used in this study anddata used in the previously published ADGC study [1]. We restricted analyses to individuals of European ancestrybecause there were an insufficient number of subjects from other ethnic groups to obtain meaningful results. Allsubjects were recruited under protocols approved by the appropriate Institutional Review Boards.

The NIA ADC Samples (ADC): The NIA ADC cohort included subjects ascertained and evaluated by theclinical and neuropathology cores of the 29 NIA-funded ADCs. Data collection is coordinated by the NationalAlzheimer’s Coordinating Center (NACC). NACC coordinates collection of phenotype data from the 29 ADCs,cleans all data, coordinates implementation of definitions of AD cases and controls, and coordinates collection ofsamples. The ADC cohort consists of 2,288 autopsy-confirmed and 913 clinically-confirmed AD cases, and 519cognitively normal elders (CNEs) with complete neuropathology data who were older than 60 years at age of death,and 744 living CNEs evaluated using the Uniform dataset (UDS) protocol [2, 3] who were documented to not havemild cognitive impairment (MCI) and were between 60 and 100 years of age at assessment.Based on the data collected by NACC, the ADGC Neuropathology Core Leaders Subcommittee derived inclusionand exclusion criteria for AD and control samples. All autopsied subjects were age ≥ 60 years at death. AD caseswere demented according to DSM-IV criteria or Clinical Dementia Rating (CDR) ≥ 1.Neuropathologic stratification of cases followed NIA/Reagan criteria explicitly, or used a similar approach whenNIA/Reagan criteria [4] were coded as not done, missing, or unknown. Cases were intermediate or high likelihoodby NIA/Reagan criteria with moderate to frequent amyloid plaques [5] and neurofibrillary tangle (NFT) Braakstage of III-VI [6, 7]. Persons with Down’s syndrome, non-AD tauopathies and synucleinopathies were excluded.All autopsied controls had a clinical evaluation within two years of death. Controls did not meet DSM-IV criteriafor dementia, did not have a diagnosis of mild cognitive impairment (MCI), and had a CDR of 0, if performed.Controls were did not meet or were low-likelihood AD by NIA/Reagan criteria, had sparse or no amyloid plaques,and a Braak NFT stage of 0 – II.ADCs sent frozen tissue from autopsied subjects and DNA samples from some autopsied subjects and from livingsubjects to the ADCs to the National Cell Repository for Alzheimer’s Disease (NCRAD). DNA was prepared byNCRAD for genotyping and sent to the genotyping site at Children’s Hospital of Philadelphia. ADC samples were

33


genotyped and analyzed in separate batches.ADC1 and ADC2 contributed 2,304 AD cases (1,761 autopsy-confirmed; 543 clinically-confirmed) and 675 CNEs(515 autopsy-confirmed; 160 clinically-confirmed), of which 1,595 autopsied-confirmed AD cases and 132 CNEswere analyzed in our previous study [1]. The ADC3 dataset contains 897 clinically-identified living cases (527with autopsy-confirmation) and 588 CNEs (4 with autopsy-confirmation) who were genotyped between July andAugust 2010.

Oregon Health and Science University (OHSU): The OHSU dataset includes 132 autopsy-confirmed AD casesand 153 deceased controls that were evaluated for dementia within 12 months prior to death (age at death >65years), which are a subset of the 193 cases and 451 controls examined in our previous study [1] meeting morestringent QC criteria in this study. Subjects were recruited from aging research cohorts at 10 NIA-funded ADCs,and did not overlap other samples assembled by the ADGC. A more extensive description of control samples canbe found elsewhere [8].

The ADNI Study (ADNI): ADNI is a longitudinal, multi-site observational study including AD, mild cognitiveimpairment (MCI), and elderly individuals with normal cognition assessing clinical and cognitive measures, MRIand PET scans (FDG and 11C PIB) and blood and CNS biomarkers. For this study, ADNI contributed data on268 AD cases with MRI confirmation of AD diagnosis and 173 healthy controls with AD-free status confirmed asof most recent follow-up. AD subjects were between the ages of 55–90, had an MMSE score of 20–26 inclusive,met NINCDS/ADRDA criteria for probable AD [9], and had an MRI consistent with the diagnosis of AD. Controlsubjects had MMSE scores between 28 and 30 and a Clinical Dementia Rating of 0 without symptoms of depres-sion, MCI or other dementia and no current use of psychoactive medications. According to the ADNI protocol,subjects were ascertained at regular intervals over 3 years, but for the purpose of our analysis we only used thefinal ascertainment status to classify case-control status. Additional details of the study design are available else-where [1, 10, 11].Data used in the preparation of this article were obtained from ADNI database (http://adni.loni.ucla.edu).The ADNI was launched in 2003 by the National Institute on Aging (NIA), the National Institute of BiomedicalImaging and Bioengineering (NIBIB), the Food and Drug Administration (FDA), private pharmaceutical compa-nies and non-profit organizations, as a $60 million, 5-year public-private partnership. The primary goal of ADNIhas been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), otherbiological markers, and clinical and neuropsychological assessment can be combined to measure the progressionof mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). Determination of sensitive and specificmarkers of very early AD progression is intended to aid researchers and clinicians to develop new treatments andmonitor their effectiveness, as well as lessen the time and cost of clinical trials. The Principal Investigator of thisinitiative is Michael W. Weiner, MD, VA Medical Center and University of California – San Francisco. ADNI is theresult of efforts of many co-investigators from a broad range of academic institutions and private corporations, andsubjects have been recruited from over 50 sites across the U.S. and Canada. The initial goal of ADNI was to recruit800 subjects but ADNI has been followed by ADNI-GO and ADNI-2. To date these three protocols have recruitedover 1500 adults, ages 55 to 90, to participate in the research, consisting of cognitively normal older individuals,people with early or late MCI, and people with early AD. The follow up duration of each group is specified in theprotocols for ADNI-1, ADNI-2 and ADNI-GO. Subjects originally recruited for ADNI-1 and ADNI-GO had theoption to be followed in ADNI-2. For up-to-date information, see www.adni-info.org.

The MIRAGE Study (MIRAGE) The MIRAGE study is a family-based genetic epidemiological study of ADthat enrolled AD cases and unaffected sibling controls at 17 clinical centers in the United States, Canada, Germany,and Greece (details elsewhere [12]), and contributed 1,262 subjects (509 AD cases and 753 CNEs), a subset of the559 cases and 788 controls that were incorporated into our prior study [1] which met more stringent QC criteria forthis study. Briefly, families were ascertained through a proband meeting the NINCDS-ADRDA criteria for definiteor probable AD. Unaffected sibling controls were verified as cognitively healthy based on a Modified Telephone

34


http://adni.loni.ucla.edu

www.adni-info.org

Interview of Cognitive Status score ≥ 86 [13].

The NCRAD/NIA-LOAD Family Study (NCRAD/NIA-LOAD): The NCRAD/NIA-LOAD Family Study [14]recruited families with two or more affected siblings with LOAD and unrelated, CNEs similar in age and ethnicbackground. A total of 1,819 cases and 1,969 CNEs from 1,802 families were recruited through the NCRAD/NIA-LOAD study, NCRAD, and the University of Kentucky and included for analysis, of which a subset of 985 casesand 881 controls were used in the previous study [1]. One case per family was selected after determining theindividual with the strictest diagnosis (definite > probable > possible LOAD). If there were multiple individualswith the strictest diagnosis, then the individual with the earliest age of onset was selected. The controls includedonly those samples that were neurologically evaluated to be normal and were not related to a study participant.

University of Miami/Vanderbilt University/Mt. Sinai School of Medicine (UM/VU/MSSM):The UM/VU/MSSM dataset contains 1,186 cases and 1,135 CNEs (new and previously published) [15, 16, 17, 18]ascertained at the University of Miami, Vanderbilt University and Mt. Sinai School of Medicine, including 409autopsy-confirmed cases and 136 controls, primarily from the Mt. Sinai School of Medicine [19]. An additional16 cases were included and 34 controls excluded from the data analyzed in the prior study [1]. Each affectedindividual met NINCDS-ADRDA criteria for probably or definite AD with age at onset greater than 60 yearsas determined from specific probe questions within the clinical history provided by a reliable family informantor from documentation of significant cognitive impairment in the medical record. Cognitively healthy controlswere unrelated individuals from the same catchment areas and frequency matched by age and gender, and had adocumented MMSE or 3MS score in the normal range. Cases and controls had similar demographics: both hadages-at-onset/ages-at-exam of 74 (± 8 standard deviations), and cases were 63% female, and controls were 61%female.

The ACT/eMERGE Studies (ACT): The ACT cohort is an urban and suburban elderly population from a stableHMO that includes 2,581 cognitively intact subjects age ≥ 65 who were enrolled between 1994 and 1998 [20,21]. An additional 811 subjects were enrolled in 2000-2002 using the same methods except oversampling clinicswith more minorities. More recently, a Continuous Enrollment strategy was initiated in which new subjects arecontacted, screened and enrolled to keep 2000 active at-risk person-years accruing in each calendar year. Thisresulted in an enrollment of 4,146 participants as of May 2009. All clinical data are reviewed at a consensusconference. Dementia onset is assigned half way between the prior biennial and the exam that diagnosed dementia.Enrollment for eMERGE Study began in 2007. A waiver of consent was obtained from the IRB to enroll deceasedACT participants. In total, ACT/eMERGE contributed data on 566 individuals with probable or possible AD (70with autopsy-confirmation) and on 1,696 CNEs (155 with autopsy-confirmation) who were included in analyses.

The GenADA Study: Data from the GenADA cohort that were analyzed included 669 AD cases and 713 CNEsascertained from nine memory referral clinics in Canada between 2002 and 2005. Patients and CNEs were of Cau-casian ancestry from Northern Europe. All patients with AD satisfied NINCDS-ADRDA and DSM-IV criteria forprobable AD with Global Deterioration Scale scores of 3-7. CNEs had MMSE test scores higher than 25 (mean29.2 ± 1.1), a Mattis Dementia Rating Scale score of ≥ 136, a Clock Test without error, and no impairments onseven instrumental activities of daily living questions from the Duke Older American Resources and Services Pro-cedures test. Data were collected under an academic-industrial grant from Glaxo-Smith-Kline, Canada by PrincipalInvestigator P. St George-Hyslop. Detailed characteristics of this cohort have been described previously [22].

The TGEN2 Study: Among the TGEN2 data analyzed were 864 clinically- and neuropathologically-characterizedbrain donors, and 493 CNEs without dementia or significant AD pathology. Of these cases and CNEs, 667 weregenotyped as a part of the TGEN1 series [23]. Samples were obtained from twenty-one different National Instituteon Aging-supported AD Center brain banks and from the Miami Brain Bank as previously described [23, 24, 25].Additional individual samples from other brain banks in the United States, United Kingdom, and the Netherlands

35


were also obtained in the same manner. The criteria for inclusion were as follows: self-defined ethnicity of Eu-ropean descent, neuropathologically confirmed AD or neuropathology present at levels consistent with status as acontrol, and age of death greater than 65. Autopsy diagnosis was performed by board certified neuropathologistsand was based on the presence or absence of the characterization of probable or possible AD. Where it was possi-ble, Braak and Braak staging and/or CERAD classification were employed. Samples derived from subjects with aclinical history of stroke, cerebrovascular disease, comorbidity with any other known neurological disease, or withthe neuropathological finding of Lewy bodies were excluded.

Mayo Clinic: All 728 cases and 1,173 controls consisted of Caucasian subjects from the United States ascer-tained at the Mayo Clinic. All subjects were diagnosed by a neurologist at the Mayo Clinic in Jacksonville, Floridaor Rochester, Minnesota. The neurologist confirmed a Clinical Dementia Rating score of 0 for all controls; caseshad diagnoses of possible or probable AD made according to NINCDS-ADRDA criteria [9]. Autopsy-confirmedsamples (221 cases, 216 CNEs) came from the brain bank at the Mayo Clinic in Jacksonville, FL and were evalu-ated by a single neuropathologist. In clinically-identified cases, the diagnosis of definite AD was made accordingto NINCDS-ADRDA criteria [9]. All AD brains analyzed in the study had a Braak score of 4.0 or greater. Brainsemployed as controls had a Braak score of 2.5 or lower but often had brain pathology unrelated to AD and patholog-ical diagnoses that included vascular dementia, frontotemporal dementia, dementia with Lewy bodies, multi-systematrophy, amyotrophic lateral sclerosis, and progressive supranuclear palsy.

The ROS/MAP Studies: ROS/MAP are two community-based cohort studies. The ROS has been on-goingsince 1993, with a rolling admission. Through July of 2010, 1,139 older nuns, priests, and brothers from across theUnited States initially free of dementia who agreed to annual clinical evaluation and brain donation at the time ofdeath completed their baseline evaluation. The MAP has been on-going since 1997, also with a rolling admission.Through July of 2010, 1,356 older persons from across northeastern Illinois initially free of dementia who agreedto annual clinical evaluation and organ donation at the time of death completed their baseline evaluation. Detailsof the clinical and neuropathologic evaluations have been previously reported [26, 27, 28, 29]. A total of 1,072persons passed genotyping QC. Of these, 296 met clinical criteria for AD at the time of their last clinical evaluationor time of death and met neuropathologic criteria for AD for those on whom neuropathologic data were available,and 776 were without dementia or MCI at the time of their last clinical evaluation or time of death and did not meetneuropathologic criteria for AD for those on whom neuropathologic data were available.

University of Pittsburgh (UP): The University of Pittsburgh dataset contains 1,271 Caucasian AD cases (ofwhich 277 were autopsy-confirmed) recruited by the University of Pittsburgh Alzheimer’s Disease Research Cen-ter, and 841 Caucasian, CNEs ages 60 and older (2 were autopsy-confirmed). All AD cases met NINCDS/ADRDAcriteria for probable or definite AD. Additional details of the cohort used for GWAS have been previously pub-lished [30].

Washington University (WU): A European American LOAD case-control dataset consisting of 339 cases and187 healthy elderly controls was used in analyses for this study. Participants were recruited as part of a longitudinalstudy of healthy aging and dementia. Diagnosis of dementia etiology was made in accordance with standard criteriaand methods [3]. Severity of dementia was assessed using the Clinical Dementia Rating scale.

The Cohort for Heart and Ageing Research in Genomic Epidemiology(CHARGE) consortium

The CHARGE consortium currently includes six large, prospective, community-based cohort studies that havegenome-wide variation data coupled with extensive data on multiple phenotypes [31]. A neurology working-group

36


arrived at a consensus on phenotype harmonization, covariate selection and analytic plans for within-study analy-ses and meta-analysis of results [32]. Consent procedures, examination and surveillance components, data security,genotyping protocols and study design at each study were approved by a local Institutional Review Board, detailsare provided below. Of the six studies, two, the Atherosclerosis Risk in Communities (ARIC) study and the Aus-trian Study of Stroke Prevention (ASPS) study were excluded from these analyses as they had not systematicallyascertained all their dementia cases at the time of this analysis. Three of the remaining 4 studies, the CardiovascularHealth Study (CHS), the Framingham Heart Study (FHS) and the Rotterdam Study had data on both the baselineprevalence, and on incident Alzheimer’s disease (AD), whereas the last, the Age, Gene/Environment Susceptibil-ity–Reykjavik Study (AGES-RS) only had data on prevalent AD.

AGES-RS: The AGES–RS is a single center prospective study based on the Reykjavik Study, which was ini-tiated in 1967 by the Icelandic Heart Association to study cardiovascular disease and risk factors. The cohortincluded men and women born 1907-35 and living in Reykjavik in 1967. In 2002, the National Institute of Agingin collaboration with the Icelandic Heart Association started the AGES study that focuses on 4 biological systems:vascular, neurocognitive, musculoskeletal and metabolism [33]. Between 2002 and 2006, it enrolled 5,764 partici-pants (42% male) who were randomly selected among the survivors (n= 8,030) of the Reykjavik Study. All cohortmembers were European Caucasians. Participants were evaluated with a questionnaire and clinical exam, had afasting sample of blood drawn, and underwent various bio-imaging measures. Of the 5,764 participants, 3,664participants were randomly selected for the GWAS. Genotyping was undertaken using the HumanCNV370-Duo(Illumina) at the Laboratory of Neurogenetics, Intramural Research Program, at the National Institute of Aging,Bethesda, Maryland. A total of 2,807 persons passed genotyping QC criteria, and, based on the methods outlinedin Section 3, were categorized as either non-demented or having Alzheimer’s disease (AD). The AGES-RS wasapproved by the Icelandic National Bioethics Committee (VSN 00-063), the Icelandic Data Protection Authority,and by the Institutional Review Board of the US National Institute on Aging, National Institutes of Health.This study included all persons with prevalent AD detected between 2002 and 2006. The Folstein Mini MentalState Examination (MMSE) and the Digit Symbol Substitution Test (DSST) were administered to all participantsand persons who scored below a pre-determined threshold on these tests (≤23 on the MMSE or ≤17 on the DSST)were administered a second, diagnostic test battery. Based on performance on the Trails B and the Rey AuditoryVerbal Learning test (RAVLT), a subset of these individuals with a RAVLT score ≤18 or Trails B score ≥8 (ratioof time taken for Trails B/Trails A corrected for the number correct) went on to a third step, which included aneurological examination and a structured informant interview about medical history and social, cognitive, anddaily functioning. MRI was acquired as a part of the core study protocol. A panel that included a geriatrician,neurologist, neuropsychologist, and neuroradiologist reached a consensus diagnosis of dementia based on the Di-agnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) guidelines. There were 319 casesof dementia diagnosed in the first 5,764 AGES participants and of these 123 also had genotyping and brain MRI.International diagnostic guidelines, including the National Institute of Neurological and Communicative Disordersand Stroke–Alzheimer Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable andpossible Alzheimer Disease and the Alzheimer’s Disease Diagnosis and Treatment Center’s (ADDTC) State ofCalifornia criteria for probable and possible vascular dementia (VaD) with or without AD, were followed. TheAGES study identified 3 subtypes: possible/probable AD without VaD (n=55, included in analysis), mixed AD(n=23, cases that met criteria for both AD and VaD, also included in analysis), and, possible/probable VaD or otherdementia without AD (n=45, excluded from this study).

Cardiovascular Health Study (CHS): The CHS is a prospective population-based cohort study of risk factorsfor vascular and metabolic disease that in 1989-90, enrolled adults aged ≥65 years, at four field centers locatedin North Carolina, California, Maryland and Pennsylvania [34]. The original predominantly Caucasian cohort of5,201 persons was recruited from a random sample of people on Medicare eligibility lists and an additional 687African-Americans were enrolled subsequently for a total sample of 5,888 [34]. Deoxyribonucleic acid (DNA)was extracted from blood samples drawn on all persons who consented to genetic testing at their baseline exami-nation in 1989-90. In 2007-2008, genotyping was performed at the General Clinical Research Center’s Phenotyp-

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ing/Genotyping Laboratory at Cedars-Sinai using the Illumina 370CNV Duo ® BeadChip system on 3,980 CHSparticipants who were free of cardiovascular disease (CVD) at baseline. The 1,908 persons excluded for prevalentCVD had prevalent coronary heart disease (n=1,195), congestive heart failure (n=86), peripheral vascular disease(n=93), valvular heart disease (n=20), stroke (n=166) or transient ischemic attack (n=56). Some persons had morethan one reason to be excluded and for these individuals only the initial exclusionary event is listed. Because theother cohorts were predominantly white, the African American CHS participants were excluded from this analysisto limit errors secondary to population stratification. Among white participants genotyping was attempted in 3,397participants and was successful in 3295 persons. A total of 742 persons were excluded as they either died prior tothe start of the CHS cognition study in 1992 (see section 3 for details), or could not be evaluated completely forbaseline cognitive status, leaving a baseline sample of 2,553 persons; an additional 31 persons were excluded forhaving dementia other than AD leaving a study sample of 2,522 persons. The CHS study protocols were approvedby the Institutional review boards at the individual participating centers.The AD sample for this study included all prevalent cases identified in 1992 and incident events identified between1992 and December 2006 [35]. Briefly, persons were examined annually from enrollment to 1999, and the ex-amination included a 30 minute screening cognitive battery. In 1992-94 and again, in 1997-99, participants wereinvited to undergo brain MRI and detailed cognitive and neurological assessment as part of the CHS CognitionStudy. Persons with prevalent dementia were identified, and all others were followed until 1999 for the develop-ment of incident dementia and AD. Since then, CHS participants at the Maryland and Pennsylvania centers haveremained under ongoing dementia surveillance [36].Beginning in 1988/89, all participants completed the Modified Mini-Mental State Examination (3MSE) and theDSST at their annual visits, and the Benton Visual Retention Test (BVRT) from 1994 to 1998. The TelephoneInterview for Cognitive Status (TICS) was used when participants did not come to the clinic. Further informationon cognition was obtained from proxies using the Informant Questionnaire for Cognitive Decline in the Elderly(IQCODE), and the dementia questionnaire (DQ). Symptoms of depression were measured with the modified ver-sion of the Center for Epidemiology Studies Depression Scale (CES-D). In 1991-94, 3,608 participants had anMRI of the brain and this was repeated in 1997-98. The CHS staff also obtained information from participants andnext-of-kin regarding vision and hearing, the circumstances of the illness, history of dementia, functional status,pharmaceutical drug use, and alcohol consumption. Data on instrumental activities of daily living (IADL), andactivities of daily living (ADL) were also collected.Persons suspected to have cognitive impairment based on the screening tests listed above underwent a neuropsy-chological and a neurological evaluation. The neuropsychological battery included the following tests: the Amer-ican version of the National Reading test (AMNART), Raven’s Coloured Progressive Matrices, California VerbalLearning Test (CVLT), a modified Rey-Osterreith figure, the Boston Naming test, the Verbal fluency test, the Blockdesign test, the Trails A and B tests, the Baddeley & Papagno Divided Attention Task, the Stroop, Digit Spanand Grooved Pegboard Tests. The results of the neuropsychological battery were classified as normal or abnormal(>1.5 standard deviations below individuals of comparable age and education) based on normative data collectedfrom a sample of 250 unimpaired subjects. The neurological exam included a brief mental status examination, aswell as a complete examination of other systems. The examiner also completed the Unified Parkinson’s DiseaseRating Scale (UPDRS) and the Hachinski Ischemic Scale. After completing the neurological exam, the neurologistclassified the participant as normal, having mild cognitive impairment (MCI), or dementia.International diagnostic guidelines, including the NINCDS-ADRDA criteria for probable and possible AD and theADDTC’s State of California criteria for probable and possible vascular dementia (VaD) with or without AD, werefollowed. CHS identified 3 subtypes: possible/probable AD without VaD (categorized as pure AD, included in allAD) and mixed AD (for cases that met criteria for both AD and VaD, included in all-AD), and, possible/probableVaD without AD (excluded from current study).

Framingham Heart Study (FHS): The FHS is a three-generation, single-site, community-based, ongoing co-hort study that was initiated in 1948. It now comprises three generations of participants including the Originalcohort followed since 1948 (n=5,209) [37], their Offspring and spouses of the offspring (n=5,216) followed since1971 [38]; and children from the largest Offspring families enrolled in 2000 (Gen 3) [39]. Participants in the

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Original and Offspring cohorts are used in these analyses, but Gen 3 participants were not included since they areyoung (mean age 40±9 years in 2000) and none had developed Alzheimer’s Disease (AD). The Original cohortenrolled 5,209 men and women who comprised two-thirds of the adult population then residing in Framingham,Massachusetts. Survivors continue to receive biennial examinations. The Offspring cohort comprises 5,124 per-sons (including 3,514 biological offspring) who have been examined approximately once every 4 years. Almost allthe FHS Original and Offspring participants are white/Caucasian. FHS participants had DNA extracted and pro-vided consent for genotyping in the 1990s. All available eligible participants were genotyped at Affymetrix (SantaClara, CA) through an NHLBI funded SNP-Health Association Resource (SHARe) project using the AffymetrixGeneChip® Human Mapping 500K Array Set and 50K Human Gene Focused Panel®. In 272 persons, smallamounts of DNA were extracted from stored whole blood and required whole genome amplification prior to geno-typing. Cell lines were available for most of the remaining participants. Genotyping was attempted in 5,293Original and Offspring cohort participants, and 4,425 persons met QC criteria. Failures (call rate <97%, extremeheterozygosity or high Mendelian error rate) were largely restricted to persons with whole-genome amplified DNAand DNA extracted from stored serum samples. In addition, since the persons with whole genome amplified DNArepresent a group of survivors who may differ from the others we included whole genome amplified status as acovariate in FHS analyses. For the prevalent analyses, we also excluded 2,268 participants who were less than 65years old at the time of the DNA draw and 14 persons with dementia other than AD; the remaining 2,143 subjectsconstitute the FHS sample for the prevalent study. A total of 806 well-genotyped persons from the Original cohort(which has been under ongoing surveillance for incident dementia since 1975) were included in the incident ADanalyses. The FHS component of this study was approved by the Institutional Review Board of the Boston MedicalCenter.The Original cohort of the FHS has been evaluated biennially since 1948, was screened for prevalent dementiaand AD in 1974-76 and has been under surveillance for incident dementia and AD since then [40, 41, 42]. TheOffspring have been examined once every 4 years and have been screened for prevalent dementia with a neuropsy-chological battery and brain MRI [43, 44]. In order to be consistent with the sampling frame for the AGES andCHS samples, we excluded FHS subjects with a baseline age <65 yrs at the time of DNA draw which was in the1990s. To minimize survival biases, Original cohort and Offspring participants who developed dementia prior tothe date of DNA draw were treated as prevalent cases, and subsequent events in the Original cohort occurring priorto December 2006 were included in the incident analyses.At each clinic exam, participants receive questionnaires, physical examinations and laboratory testing; betweenexaminations they remain under surveillance (regardless of whether or not they live in the vicinity) via physicianreferrals, record linkage and annual telephone health history updates. Methods used for dementia screening andfollow-up have been previously described [40, 45]. Briefly, surviving cohort members who attended biennial ex-amination cycles 14 and 15 (May 1975-November 1979) were administered a standardized neuropsychological testbattery to establish a dementia-free cohort. Beginning at examination cycle 17 (1982), the MMSE was adminis-tered biennially to the cohort. A MMSE score below the education-specific cutoff score, a decline of 3 or morepoints on subsequent administrations, a decline of more than 5 points compared with any previous examination, ora physician or family referral prompted further in-depth testing. The Offspring cohort that was enrolled in 1971has undergone 8 re-examinations, one approximately every 4 years. Starting at the 2nd Offspring examination,participants were questioned regarding any subjective memory complaints and since the 5th Offspring examinationparticipants have been administered the MMSE at each visit. In addition concurrent with the 7th and 8th Offspringexaminations (between 1999 and 2004 and then again between 2005 and 2009) surviving Original cohort and alleligible and consenting Offspring participants have undergone volumetric brain MRI and neuropsychological test-ing [43, 44]. The neuropsychological test battery included the Reading subtest of the Wide Range AchievementTest (WRAT-3), the Logical Memory and the Paired Associates Learning tests from the Wechsler Memory Scale,the Visual Reproduction and Hooper Visual Organization Tests, Trails A and B, the Similarities subtest from theWechsler Adult Intelligence test, the 30-iterm version of the Boston Naming Test and at the second assessmentonly, the Digit Span, Controlled Word Association and Clock Drawing Tests. Offspring participants suspected tohave cognitive impairment based on their MMSE scores, participant, family or physician referral, hospital recordsor performance in the neuropsychological test battery described above were referred for more detailed neuropsy-

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chological and neurological evaluation.Each participant thus identified underwent baseline neurologic and neuropsychological examinations. Neurologists(trained in geriatric behavioral assessment) supplemented their clinical assessment with a few structured cognitivetests and administered the Clinical Dementia Rating (CDR). Persons were reassessed systematically for the onsetof at least mild dementia. A panel consisting of at least 1 neurologist (S.A., P.A.W., or S.S.) and 1 neuropsy-chologist (R.A.) reviewed all available medical records to arrive at a final determination regarding the presenceor absence of dementia, the date of onset of dementia, and the type of dementia. For this determination, we useddata from the neurologist’s examination, neuropsychological test performance, Framingham Study records, hos-pital records, information from primary care physicians, structured family interviews, computed tomography andmagnetic resonance imaging records, and autopsy confirmation when available. All individuals identified as hav-ing dementia satisfied the DSM-IV criteria, had dementia severity equivalent to a CDR of 1 or greater, and hadsymptoms of dementia for at least 6 months. All individuals identified as having Alzheimer-related dementia metthe NINCDS-ADRDA criteria for definite, probable, or possible AD. Vascular Dementia was diagnosed using theADDTC criteria but the presence of vascular dementia did not disqualify a participant from obtaining a concomi-tant diagnosis of AD if indicated. The recruitment of Original cohort participants at FHS had occurred long beforethe DNA collection with the result that the majority of dementia events in the FHS (although ascertained prospec-tively) were prevalent at the time of DNA collection or these persons had died prior to DNA draw and were thusexcluded from analyses of incident disease. Due to the limited number of incident dementia and AD events in theFramingham Offspring only the Original cohort were included in our analyses of incident events.

Rotterdam Study: The Rotterdam Study enrolled inhabitants from a district of Rotterdam (Ommoord) aged ≥55years (N=7,983, virtually all white) at the baseline examination in 1990-93 when blood was drawn for genotyp-ing [46, 47]. It aims to examine the determinants of disease and health in the elderly with a focus on neurogeriatric,cardiovascular, bone, and eye disease [8]. All inhabitants of Ommoord aged ≥55 years (n = 10,275) were invitedand the participation rate was 78%. All participants gave written informed consent to retrieve information fromtreating physicians. Baseline measurements were obtained from 1990 to 1993 and consisted of an interview athome and two visits to the research center for physical examination. Survivors have been re-examined three times:in 1993-1995, 1997-1999, and 2002-2004. All persons attending the baseline examination in 1990-93 consented togenotyping and had DNA extracted. This DNA was genotyped using the Illumina Infinium II HumanHap550chipv3·0® array in 2007-2008 according to the manufacturer’s protocols. Genotyping was attempted in persons withhigh-quality extracted DNA (n=6,449). From these 6,449, samples with low call rate (<97.5%, n=209), withexcess autosomal heterozygosity (>0.336, n=21), with sex-mismatch (n=36), or if there were outliers identifiedby the IBS clustering analysis (>3 standard deviations from population mean, n=102 or IBS probabilities >97%,n=129) were excluded from the study population with some persons meeting more than one exclusion criterion;in total, 5,974 samples were available with good quality genotyping data, 42 persons were excluded since they didnot undergo cognitive screening at baseline, hence their cognitive status was uncertain. An additional 61 personswere excluded because they suffered from dementia other than AD at baseline. Thus there were 5,871 personsincluded in the prevalent analysis and after exclusion of 171 persons with prevalent AD, 5,700 persons were fol-lowed for incident AD and other dementia. The Rotterdam Study (including its brain magnetic resonance imaging(MRI) and neurological components) has been approved by the institutional review board (Medical Ethics Commit-tee) of the Erasmus Medical Center and the Netherlands Ministry of Health, Welfare and Sports Participants werescreened for prevalent dementia in 1990-93 using a three-stage process; those free of dementia remained undersurveillance for incident dementia, a determination made using records linkage and assessment at three subsequentre-examinations [48]. We included all prevalent cases and all incident events up to 31st December 2007.Screening was done with the MMSE and GMS organic level for all persons. Screen-positives (MMSE <26 or Geri-atric Mental Schedule (GMS) organic level >0) underwent the CAMDEX. Persons who were suspected of havingdementia underwent more extensive neuropsychological testing. When available, imaging data were used. In addi-tion, all participants have been continuously monitored for major events (including dementia) through automatedlinkage of the study database with digitized medical records from general practitioners, the Regional Institute forOutpatient Mental Health Care and the municipality. In addition physician files from nursing homes and general

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practitioner records of participants who moved out of the Ommoord district were reviewed twice a year. For sus-pected dementia events, additional information (including neuroimaging) was obtained from hospital records andresearch physicians discussed available information with a neurologist experienced in dementia diagnosis and re-search to verify all diagnoses. Dementia was diagnosed in accordance with internationally accepted criteria fordementia (Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition, DSM-III-R), and ADusing the NINCDS-ADRDA criteria for possible, probable and definite AD. The National Institute of NeurologicalDisorders and Stroke–Association Internationale pour la Recherche et l’Enseignement en Neurosciences (NINDS-AIREN) criteria were used to diagnose vascular dementia. The final diagnosis was determined by a panel of aneurologist, neurophysiologist, and research physician and the diagnoses of AD and VaD were not mutually exclu-sive.

European Alzheimer’s Disease Initiative (EADI) consortium

All the 2,243 AD cases were ascertained by neurologists from Bordeaux, Dijon, Lille, Montpellier, Paris, Rouen,and were identified as French Caucasian [49, 50]. Clinical diagnosis of probable AD was established according tothe DSM-III-R and NINCDS-ADRDA criteria. Controls were selected from the 3C Study [50]. This cohort is apopulation-based, prospective (7-years follow-up) study of the relationship between vascular factors and dementia.It has been carried out in three French cities: Bordeaux (southwest France), Montpellier (southeast France) andDijon (central eastern France). A sample of non-institutionalised, over-65 subjects was randomly selected from theelectoral rolls of each city. Between January 1999 and March 2001, 9,686 subjects meeting the inclusion criteriaagreed to participate. Following recruitment, 392 subjects withdrew from the study. Thus, 9,294 subjects werefinally included in the study (2,104 in Bordeaux, 4,931 in Dijon and 2,259 in Montpellier). Genomic DNA samplesof 7,200 individuals were transferred to the French Centre National de Génotypage (CNG). First stage samples thatpassed DNA quality control were genotyped with Illumina Human 610-Quad BeadChips. At the end we removed308 samples because they were found to be first- or second-degree relatives of other study participants, or wereassessed non-European descent based on genetic analysis using methods described in [51]. In this final sample, at7 years of follow-up, 459 individuals suffered from AD with 97 prevalent and 362 incident cases. These AD caseswere included as cases in the EADI stage 1 dataset. We retained the other individuals as controls (n=6,017).

Genetic and Environmental Risk in Alzheimer’s Disease (GERAD) consortium

The GERAD sample comprises 3,177 AD cases and 7,277 controls with available age and gender data (see Sup-plementary Table 7) [52]. Cases and elderly screened controls were recruited by the Medical Research Council(MRC) Genetic Resource for AD (Cardiff University; Institute of Psychiatry, London; Cambridge University; Trin-ity College Dublin), the Alzheimer’s Research Trust (ART) Collaboration (University of Nottingham; University ofManchester; University of Southampton; University of Bristol; Queen’s University Belfast; the Oxford Project toInvestigate Memory and Ageing (OPTIMA), Oxford University); Washington University, St Louis, United States;MRC PRION Unit, University College London; London and the South East Region AD project (LASER-AD),University College London; Competence Network of Dementia (CND) and Department of Psychiatry, Universityof Bonn, Germany; the National Institute of Mental Health (NIMH) AD Genetics Initiative. 6,129 population con-trols were drawn from large existing cohorts with available GWAS data, including the 1958 British Birth Cohort(1958BC) (http://www.b58cgene.sgul.ac.uk), the KORA F4 Study and the Heinz Nixdorf Recall Study. AllAD cases met criteria for either probable (NINCDS-ADRDA, DSM-IV) or definite (CERAD) AD All elderly con-trols were screened for dementia using the MMSE or ADAS-cog, were determined to be free from dementia atneuropathological examination or had a Braak score of 2.5 or lower. Genotypes from all cases and 4,617 controlswere previously included in the AD GWAS by Harold and colleagues [52]. Genotypes for the remaining 2,660population controls were obtained from WTCCC2.

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http://www.b58cgene.sgul.ac.uk

Stage 2 case-control studies

Additional 22,618 case-control samples were obtained for replication from centres in Austria (1 centre), Belgium(1 centre), Finland (1 centre), Germany (4 centres), Greece (1 centre), Hungary (1 centre), Italy (8 centres), Spain(7 centres), Sweden (2 centres), the UK (5 centres) and the USA (1 centre) (see Table 1 for description by countriesand Supplementary Table 8 for description by centre). Clinical diagnoses of probable AD were all establishedaccording to the DSM-III-R and NINCDS-ADRDA criteria. Controls were defined as subjects without DMS-III-Rdementia criteria and with integrity of their cognitive functions (MMS >25). Each laboratory was asked to send2.5 µg of genomic DNA at 50 ng/µl.Genotyping of ASPS Austrian control samples was performed using the Illumina Human610-Quad BeadChip. Weexcluded samples with low call rate (<98%), with excess autosomal heterozygosity (>0.350), with sex-mismatch,or as outliers identified by the IBS clustering analysis (>3 standard deviations from population mean or IBS prob-abilities >97%). Imputation was done using 1000G phase 1 interim (June 2011) data with the IMPUTE2 software.German individuals from Bonn centre were genotyped using the Illumina Omni1-Quad chip. Individuals with agenotype call rate worse than 99% or identified as outliers by a PCA were excluded. Identical DNAs and relation-ships between probands were checked by computation of the IBS-matrix and we removed one individual from eachpair with an IBS that was 4 standard deviations higher than the average IBS of all pairs of individuals. Some ofthe AD patients were part of the original GERAD study. All doubled individuals were identified via IBS-analysisand were excluded. Imputation was performed with IMPUTE2 using 1,000 Genomes reference data (Feb 2012release).

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46


EADI consortium

Annick Alpérovitch1, Anne Boland2, Marc Delépine2, Bruno Dubois3, Emmanuelle Duron4, Jacques Epelbaum5,Caroline Van Cauwenberghe6,7, Sebastiaan Engelborghs7,8, Rik Vandenberghe9,10, Peter P. De Deyn7,8, RaffaeleFerri11, Carmelo Romano11, Carlo Caltagirone12, Maria Donata Orfei12, Antonio Ciaramella12, Elio Scarpini13,14,Chiara Fenoglio13,14, Gabriele Siciliano15, Ubaldo Bonuccelli15, Silvia Bagnoli16,17, Laura Bracco16,17,Valentina Bessi16,17, Roberta Cecchetti18,19, Patrizia Bastiani18,19, Alessio Squassina20, Davide Seripa21, AnaFrank-García22,23,24, Isabel Sastre25,23,24, Rafael Blesa26,27, Daniel Alcolea26,27, Marc Suárez-Calvet26,27, PascualSánchez-Juan28, Carmen Muñoz Fernandez29, Yolanda Aladro Benito29, Håkan Thonberg30, Charlotte Forsell31,Lena Lilius31, Anne Kinhult-Ståhlbom30, Vilmantas Giedraitis32, Lena Kilander32, RoseMarie Brundin32, LetiziaConcari33,34, Seppo Helisalmi35,36, Anne Maria Koivisto35,36, Annakaisa Haapasalo35,36, Vincenzo Solfrizzi37,Vincenza Frisardi38, Jurg Ott39.

1. Inserm U708, Victor Segalen University, F-33076, Bordeaux, France2. Centre National de Genotypage, Institut Genomique, Commissariat à l’énergie Atomique, Evry, France3. IM2A - CRicm-UMRS975, AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France4. CMRR Paris Sud Ile-de-France, service de gériatrie, Hôpital Broca, 54-56 rue Pascal, 75013 Paris, France5. UMR 894 Inserm, Psychiatry and Neurosciences Center, Paris, France6. Neurodegenerative Brain Diseases Group, Department of Molecular Genetics, VIB, Antwerp, Belgium7. Institute Born-Bunge, University of Antwerp, Antwerp, Belgium8. Department of Neurology and Memory Clinic, Hospital Network Antwerp, Antwerp, Belgium9. Laboratory for Cognitive Neurology, Department of Neurology, University of Leuven, Leuven, Belgium10. Department of Neurology and Memory Clinic, University Hospitals Leuven Gasthuisberg, Leuven, Belgium11. IRCCS Associazione Oasi Maria SS, Troina, Italy12. Clinical and Behavioral Neurology, Fondazione Santa Lucia, Roma ,Italy13. University of Milan, Milan, Italy14. Fondazione Cà Granda, IRCCS Ospedale Policlinico, Milan, Italy15. Neurological Clinic, University of Pisa, Italy16. NEUROFARBA Department of Neuroscience, Psychology, Drug Research and Child Health, University ofFlorence, Florence, Italy17. Centro di Ricerca, Trasferimento e Alta Formazione DENOTHE, University of Florence, Florence, Italy18. Section of Gerontology and Geriatrics, Department of Clinical and Experimental Medicine Perugia, Italy19. University of Perugia, Perugia, Italy20. Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Science, University of Cagliari,Cagliari, Italy21. Gerontology and Geriatrics Research Laboratory, I.R.C.C.S. Casa Sollievo della Sofferenza, San GiovanniRotondo (FG), Italy22. Neurology Service; Hospital Universitario La Paz (UAM), Madrid, Spain23. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid,Spain24. Instituto de Investigación Sanitaria «Hospital la Paz» (IdIPaz), Madrid, Spain25. Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Madrid, Spain26. Neurology Department. IIB Sant Pau. Sant Pau Hospital. Universitat Autònoma de Barcelona. Barcelona,Spain.27. Center for Networker Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Spain.28. Neurology Service and CIBERNED, «Marqués de Valdecilla» University Hospital (University of Cantabriaand IFIMAV), Santander, Spain29. Department of Neurology, Hospital Universitario Dr. Negrin, Las Palmas de Gran Canaria, Spain30. Dept Geriatric Medicine, Genetics Unit, Karolinska University Hospital Huddinge, S-14186 Stockholm,

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Sweden31. Karolinska Institutet, Dept Neurobiology, Care Sciences and Society, KIADRC, Novum floor 5, S14186Stockholm, Sweden32. Dept. of Public Health/Geriatrics, Uppsala University, Uppsala, Sweden33. Department of Neuroscience-University of Parma-Italy, Parma, Italy34. Center for Cognitive Disorders AUSL, Parma, Italy35. Institute of Clinical Medicine - Neurology, University of Eastern Finland, FIN-70211, Kuopio, Finland36. Department of Neurology, Kuopio University Hospital, FIN-70211 Kuopio, Finland37. Department of Geriatrics, Center for Aging Brain ,University of Bari, Bari, Italy38. Department of Neurosciences and Sensory Organs, Aldo Moro University of Bari, Bari, Italy39. Laboratory of Statistical Genetics, The Rockfeller University, 1230 York Avenue, New York, NY, 10065, USA

48


ADGC consortium

Regina M Carney1, Deborah C Mash2, Marilyn S Albert3, Roger L Albin4,5, Liana G Apostolova6, Steven EArnold7, Michael M Barmada8, Lisa L Barnes9,10, Thomas G Beach11, Eileen H Bigio12, Thomas D Bird13,Bradley F Boeve14, James D Bowen15, Adam Boxer16, James R Burk17, Nigel J Cairns18, Chuanhai Cao19, Chris SCarlson20, Steven L Carroll21, Lori B Chibnik22,23, Helena C Chui24, David G Clark25, Jason Corneveaux26, DavidG Cribbs27, Charles DeCarli28, Steven T DeKosky29, F Yesim Demirci8, Malcolm Dick30, Dennis W Dickson31,Ranjan Duara32, Nilufer Ertekin-Taner31,33, Kenneth B Fallon21, Martin R Farlow34, Steven Ferris35, Matthew PFrosch36, Douglas R Galasko37, Mary Ganguli38, Marla Gearing39,40, Daniel H Geschwind41, Bernardino Ghetti42,Sid Gilman4, Jonathan D Glass43, John H Growdon44, Ronald L Hamilton45, Lindy E Harrell46, Elizabeth Head47,Lawrence S Honig48, Christine M Hulette49, Bradley T Hyman44, Gail P Jarvik50,51, Gregory A Jicha52,Lee-Way Jin53, Anna Karydas16, John SK Kauwe54, Jeffrey A Kaye55,56, Ronald Kim57, Edward H Koo37, Neil WKowall58,60, Joel H Kramer60, Patricia Kramer55,61, Frank M LaFerla62, James J Lah43, James B Leverenz64,Allan I Levey42, Ge Li64, Andrew P Lieberman65, Constantine G Lyketsos66, Wendy J Mack67, Daniel C Marson46,Frank Martiniuk68, Eliezer Masliah37,69, Wayne C McCormick70, Susan M McCurry71, Andrew N McDavid20, AnnC McKee58,59, Marsel Mesulam72, Bruce L Miller16, Carol A Miller73, Joshua W Miller74, John C Morris18,75,The Alzheimer’s Disease Neuroimaging Initiative∗, Jill R Murrell41,76, John M Olichney77, Vernon S Pankratz78,Joseph E Parisi79,81, Elaine Peskind64, Ronald C Petersen81, Aimee Pierce27, Wayne W Poon29, HuntingtonPotter82, Joseph F Quinn55, Ashok Raj82, Murray Raskind64, Eric M. Reiman26,83,84, Barry Reisberg35,85, JohnM Ringman6, Erik D Roberson46, Howard J Rosen16, Roger N Rosenberg86, Mary Sano87, Andrew J Saykin42,88,Julie A Schneider9,89, Lon S Schneider6,90, William W Seeley16, Amanda G Smith82, Joshua A Sonnen63,Salvatore Spina42, Robert A Stern58, Rudolph E Tanzi44, John Q Trojanowski91, Juan C Troncoso92, Vivianna MVan Deerlin91, Linda J Van Eldik93, Harry V Vinters6,94, Jean Paul Vonsattel95, Sandra Weintraub72, Kathleen AWelsh-Bohmer96,97, Jennifer Williamson48, Randall L Woltjer98, Chang-En Yu70, Robert Barber99.

1. The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, 33124, USA2. Department of Neurology, University of Miami, Miami, FL, 33124, USA3. Department of Neurology, Johns Hopkins University, Baltimore, MD, 21218, USA4. Department of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA5. Geriatric Research, Education and Clinical Center (GRECC), VA Ann Arbor Healthcare System (VAAAHS),Ann Arbor, MI, 48109, USA6. Department of Neurology, University of California Los Angeles, Los Angeles, CA, 94607, USA7. Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104,USA8. Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, 15213, USA9. Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA10. Department of Behavioral Sciences, Rush University Medical Center, Chicago, IL, 60612, USA11. Civil Laboratory for Neuropathology, Banner Sun Health Research Institute, Phoenix, AZ, 85351, USA12. Department of Pathology, Northwestern University, Chicago, IL, 60208, USA13. Department of Neurology, University of Washington, Seattle, WA, 98195, USA14. Department of Neurology, Mayo Clinic, Rochester, MN, 55902, USA15. Swedish Medical Center, Seattle, WA, 98195, USA16. Department of Neurology, University of California San Francisco, San Francisco, CA, 94122, USA17. Department of Medicine, Duke University, Durham, NC, 27710, USA18. Department of Pathology and Immunology, Washington University, St. Louis, MO, 63130, USA19. USF Health Byrd Alzheimer’s Institute, University of South Florida, Tampa, CA, 33620, USA20. Fred Hutchinson Cancer Research Center, Seattle, WA, 98195, USA21. Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA22. Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Department of

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Neurology & Psychiatry, Bringham and Women’s Hospital, Harvard Medical School, Boston, MA, 02215, USA23. Program in Medical and Population Genetics, Broad Institute, Boston, MA, 02215, USA24. Department of Neurology, University of Southern California, Los Angeles, CA, 94607, USA25. Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA26. Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, 85004, USA27. Department of Neurology, University of California Irvine, Irvine, CA, 92617, USA28. Department of Neurology, University of California Davis, Sacramento, CA, 95616, USA29. University of Virginia School of Medicine, Charlottesville, VA, 22903, USA30. Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA,92617, USA31. Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 55902, USA32. Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL,10029, USA33. Department of Neurology, Mayo Clinic, Jacksonville, FL, 55902, USA34. Department of Neurology, Indiana University, Indianapolis, IN, 46202, USA35. Department of Psychiatry, New York University, New York, NY, 10027, USA36. C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Charlestown, MA, 02114, USA37. Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA38. Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA39. Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, 30329, USA40. Emory Alzheimer’s Disease Center, Emory University, Atlanta, GA, 30329, USA41. Neurogenetics Program, University of California Los Angeles, Los Angeles, CA, 94607, USA42. Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN, 46202, USA43. Department of Neurology, Emory University, Atlanta, GA, 30329, USA44. Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, 02215,USA45. Department of Pathology (Neuropathology), University of Pittsburgh, Pittsburgh, PA, 15213, USA46. Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA47. Sanders-Brown Center on Aging, Department of Molecular and Biomedical Pharmacology, University ofKentucky, Lexington, KY, 40506, USA48. Taub Institute on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Columbia University,New York, NY, 10027, USA49. Department of Pathology, Duke University, Durham, NC, 27710, USA50. Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA51. Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, 98195, USA52. Sanders-Brown Center on Aging, Department Neurology, University of Kentucky, Lexington, KY, 40506, USA53. Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, 95616,USA54. Department of Biology, Brigham Young University, Provo, UT 02215, USA55. Department of Neurology, Oregon Health & Science University, Portland, OR, 97239, USA56. Department of Neurology, Portland Veterans Affairs Medical Center, Portland, OR, 97239, USA57. Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, CA, 92617, USA58. Department of Neurology, Boston University School of Medicine, Boston, MA, 02215, USA59. Department of Pathology, Boston University School of Medicine, Boston, MA, 02215, USA60. Department of Neuropsychology, University of California San Francisco, San Francisco, CA, 94122, USA61. Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, 97239,USA62. Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, 92617, USA63. Department of Pathology, University of Washington, Seattle, WA, 98195, USA64. Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, 98195, USA

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65. Department of Pathology, University of Michigan, Ann Arbor, MI, 48109, USA66. Department of Psychiatry, Johns Hopkins University, Baltimore, MD, 21218, USA67. Department of Preventive Medicine, University of Southern California, Los Angeles, CA, 94607, USA68. Department of Medicine - Pulmonary, New York University, New York, NY, 10027, USA69. Department of Pathology, University of California San Diego, La Jolla, CA, 92093, USA70. Department of Medicine, University of Washington, Seattle, WA, 98195, USA71. School of Nursing Northwest Research Group on Aging, University of Washington, Seattle, WA, 98195, USA72. Cognitive Neurology and Alzheimer’s Disease Center, Northwestern University, Chicago, IL, 60208, USA73. Department of Pathology, University of Southern California, Los Angeles, CA, 94607, USA74. Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, 95616,USA75. Department of Neurology, Washington University, St. Louis, MO, 98101, USA76. Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, 46202, USA77. Department of Neurology, University of California Davis, Sacramento, CA, 95616, USA78. Department of Biostatistics, Mayo Clinic, Rochester, MN, 55902, USA79. Department of Anatomic Pathology, Mayo Clinic, Mayo Clinic, Rochester, MN, 55902, USA80. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55902, USA81. Department of Neurology, Mayo Clinic, Rochester, MN, 55902, USA82. USF Health Byrd Alzheimer’s Institute, University of South Florida, Tampa, FL, 33613, USA83. Arizona Alzheimer’s Consortium, Department of Psychiatry, University of Arizona, Phoenix, AZ, 85004, USA84. Banner Alzheimer’s Institute, Phoenix, AZ, 85004, USA85. Alzheimer’s Disease Center, New York University, New York, NY, 10027, USA86. Department of Neurology, University of Texas Southwestern, Dallas, TX, 75390, USA87. Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, 10027, USA88. Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, 46202, USA89. Department of Pathology (Neuropathology), Rush University Medical Center,Chicago, IL, 60208, USA90. Department of Psychiatry, University of Southern California, Los Angeles, CA, 94607, USA91. Department of Pathology and Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine,Philadelphia, PA, 19104, USA92. Department of Pathology, Johns Hopkins University, Baltimore, MD, 21218, USA93. Sanders-Brown Center on Aging, Department of Anatomy and Neurobiology, University of Kentucky,Lexington, KY, 40506, USA94. Department of Pathology & Laboratory Medicine, University of California Los Angeles, Los Angeles, CA,94607, USA95. Taub Institute on Alzheimer’s Disease and the Aging Brain, Department of Pathology, Columbia University,New York, NY, 10027, USA96. Department of Medicine, Duke University, Durham, NC, 27710, USA97. Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, 27710, USA98. Department of Pathology, Oregon Health & Science University, Portland, OR, 97239, USA99. Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth,TX, 76102, USA

∗Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative(ADNI) database (http://adni.loni.ucla.edu). As such, the investigators within the ADNI contributed tothe design and implementation of ADNI and/or provided data but did not participate in analysis or writing of thisreport. A complete listing of ADNI investigators can be found at: http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

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http://adni.loni.ucla.edu

http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

CHARGE consortium

Rhoda Au1, Philip A Wolf1, Alexa Beiser2, Stephanie Debette3,4, Qiong Yang2, Galit Weinstein1, Andrew DJohnson5, Jing Wang2, Andre G Uitterlinden6,7,8, Fernando Rivadeneira6, Peter J Koudstaal9, William TLongstreth Jr10,11,12, James T Becker13, Lewis H Kuller14, Thomas Lumley15, Kenneth Rice16, Melissa Garcia17,Thor Aspelund18, Josef JM Marksteiner19, Peter Dal-Bianco20, Anna Maria Töglhofer21, Paul Freudenberger21,Gerhard Ransmayr22, Thomas Benke23, Anna M Toeglhofer21, Jan Bressler24, Monique MB Breteler25,Myriam Fornage26, Isabel Hernández27, Maitee Rosende Roca27, Ana Mauleón27, Montserrat Alegret27, ReposoRamírez-Lorca28, Antonio González-Perez28.

1. Department of Neurology, Boston University School of Medicine, Boston, MA 2118, USA2. Department of Biostatistics, Boston University School of Public Health, Boston, MA 2118, USA3. Department of Neurology, Boston University School of Medicine, Boston, MA 2118, USA4. UMR744 Inserm, Lille, France5. NHLBI Center for Cardiovascular Genomics, the Framingham Study, Framingham, MA 1702, USA6. Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, 3000 CA, TheNetherlands (Uiterlinden)7. Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, TheNetherlands (Uiterlinden)8. Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands (Uiterlinden)9. Department of Neurology, Erasmus MC University Medical Center, Rotterdam 3000 CA, The Netherlands10. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101,USA11. Department of Epidemiology, University of Washington, Seattle, WA 98101, USA12. Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, USA13. The Departments of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA14. Departments of Medicine and Epidemiology, University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA15. Department of Statistics, University of Auckland, Auckland, New Zealand.16. Department of Biostatistics, University of Washington, School of Medicine, Seattle, WA 98101, USA17. Laboratory of Epidemiology, Demography and Biometry, National Institute on Aging, Bethesda, MD, 20892,USA18. The Icelandic Heart Association, Landspitali-University Hospital, Reykjavik, Iceland19. Department of Psychiatry and Psychotherapy, General Hospital, Hall, 6060, Austria20. Department of Neurology, Medical University of Vienna, Vienna, 1090, Austria21. Institute for Molecular Biology and Biochemistry, Medical University of Graz, Graz, 8010, Austria22. Department of Neurology and Psychiatry,General Hospital Linz, Austria, Linz, 4020, Austria23. Clinic of Neurology, Medical University Innsbruck, Innsbruck, 6020, Austria24. School of Public Health, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA25. German Center for Neurodegenerative diseases (DZNE), Bonn, 53175, Germany26. Institute of Molecular Medicine and School of Public Health Division of Epidemiology Human Genetics andEnvironmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA27. Memory Clinic of Fundació ACE. Institut Català de Neurociències Aplicades, Barcelona, 8029, Spain28. Departamento de Genómica Estructural . Neocodex, Sevilla, 8029, Spain

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GERAD consortium

Jade Chapman1, Alexandra Stretton1, Angharad Morgan1, Patrick G Kehoe2, Christopher Medway3, JennyLord3, James Turton3, Nigel M Hooper4, Emma Vardy5, Jason D Warren6, Jonathan M Schott6, JamesUphill7, Natalie Ryan6, Martin Rossor6,7, Yoav Ben-Shlomo8, Daniilidou Makrina9, Olymbia Gkatzima9, MichelleLupton10, Maria Koutroumani9, Despoina Avramidou9, Antonia Germanou9, Frank Jessen11, Steffi Riedel-Heller12,Martin Dichgans13, Reiner Heun14, Heike Kölsch14, Britta Schürmann14, Christine Herold15, André Lacour15,Dmitriy Drichel15, Per Hoffmann16, Johannes Kornhuber17, Wei Gu18, Thomas Feulner18, Hendrik van denBussche19, Brian Lawlor20, Aoibhinn Lynch20, David Mann21, A David Smith22, Donald Warden22, GordonWilcock22, Isabella Heuser23, Jens Wiltfang24, Lutz Frölich25, Michael Hüll26, Kevin Mayo27, Gill Livingston28,Nicholas J Bass28, Hugh Gurling28, Andrew McQuillin28, Rhian Gwilliam29, Panagiotis Deloukas29, AmmarAl-Chalabi30, Christopher E Shaw30, Andrew B Singleton31, Rita Guerreiro31, Karl-Heinz Jöckel32, NormanKlopp33, H-Erich Wichmann33, Dennis W Dickson34, Neill R Graff-Radford34, Li Ma34, Gina Bisceglio34,Elizabeth Fisher35, Nick Warner36, Stuart Pickering-Brown37.

1. Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics &Genomics, Cardiff University, UK2. University of Bristol Institute of Clinical Neurosciences, School of Clinical Sciences, Frenchay Hospital,Bristol, UK3. Institute of Genetics, Queen’s Medical Centre, University of Nottingham, UK.4. Institute of Molecular and Cellular Biology, Faculty of Biological Sciences, LIGHT Laboratories, University ofLeeds, Leeds, UK.5. Institute for Ageing and Health, Newcastle University, Biomedical Research Building, Campus for Ageing andVitality, Newcastle upon Tyne, UK6. Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London,UK.7. MRC Prion Unit, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.8. School of Social and Community Medicine, University of Bristol, Bristol, UK9. Aristotle University of Thessaloniki, Despere 3, Thessaloniki, 54621, Greece10. King’s College London, Institute of Psychiatry, Department of Neuroscience, De Crespigny Park, DenmarkHill, London, UK11. Department of Psychiatry and Psychotherapy, University of Bonn, Germany and German Center forNeurodegenerative Diseases (DZNE, Bonn), Bonn, Germany12. Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany13. Institute for Stroke and Dementia Research, Klinikum der Universität München, Munich, Germany andGerman Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany14. Department of Psychiatry and Psychotherapy, University of Bonn, Germany15. Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE, Bonn), Bonn, Germany16. Division of Medical Genetics, University Hospital and Department of Biomedicine, University of Basel, Basel,Switzerland17. Department of Psychiatry, University of Erlangen, Nürnberg, Germany18. Dept. Of Psychaitry, University Hospital, Saarland, Germany19. Institute of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Germany20. Mercer’s Institute for Research on Aging, St. James Hospital and Trinity College, Dublin, Ireland21. Clinical Neuroscience Research Group, Greater Manchester Neurosciences Centre, University of Manchester,Salford, UK22. Oxford Project to Investigate Memory and Ageing (OPTIMA), University of Oxford, Level 4, John RadcliffeHospital, Oxford OX3 9DU, UK23. Department of Psychiatry, Charité, Berlin, Germany

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24. LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, University Duisburg-Essen, Germany25. Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany.26. Department of Psychiatry, University of Frankfurt am Main, Frankfurt am Main, Germany27. Departments of Psychiatry, Neurology and Genetics, Washington University School of Medicine, St Louis,MO 63110, USA28. Department of Mental Health Sciences, University College London, UK.29. The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.30. MRC Centre for Neurodegeneration Research, Department of Clinical Neuroscience, King’s College London,Institute of Psychiatry, London, SE5 8AF, UK.31. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892,USA.32. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, UniversityDuisburg-Essen, Hufelandstr. 55, D-45147 Essen, Germany.33. Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health,Neuherberg, Germany34. Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, 32224, USA35. Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK36. Somerset Partnership NHS Trust, Somerset, UK37. Institute of Brain, Behaviour and Mental Health, Faculty of Human and Medical Sciences, University ofManchester, Manchester, UK

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Acknowledgements

This work was made possible by the generous participation of the control subjects, the patients, and their families.The i-Select chips was funded by the French National Foundation on Alzheimer’s disease and related disorders.The French National Fondation on Alzheimer’s disease and related disorders supported several I-GAP meetingsand communications. Data management involved the Centre National de Génotypage,and was supported by theInstitut Pasteur de Lille, Inserm, FRC (fondation pour la recherche sur le cerveau) and Rotary. This work hasbeen developed and supported by the LABEX (laboratory of excellence program investment for the future) DIS-TALZ grant (Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer’s disease) andby the LABEX GENMED grant (Medical Genomics). The French National Foundation on Alzheimer’s diseaseand related disorders and the Alzheimer’s Association (Chicago, IL) grant supported IGAP in-person meetings,communication and the Alzheimer’s Association (Chicago, IL) grant provided some funds to each consortium foranalyses.

EADIWe thank Dr. Anne Boland (CNG) for her technical help in preparing the DNA samples for analyses. This workwas supported by the National Foundation for Alzheimer’s disease and related disorders, the Institut Pasteur deLille and the Centre National de Génotypage.The Three-City Study was performed as part of a collaboration between the Institut National de la Santé et de laRecherche Médicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthélabo. The Fondationpour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also fundedby the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de laLongévité, Agence Française de Sécurité Sanitaire des Produits de Santé, the Aquitaine and Bourgogne RegionalCouncils, Agence Nationale de la Recherche, ANR supported the COGINUT and COVADIS projects. Fondation deFrance and the joint French Ministry of Research/INSERM «Cohortes et collections de données biologiques» pro-gramme. Lille Génopôle received an unconditional grant from Eisai. The Three-city biological bank was developedand maintained by the laboratory for genomic analysis LAG-BRC - Institut Pasteur de Lille.Belgium sample collection: The patients were clinically and pathological characterized by the neurologists Sebasti-aan Engelborghs, Rik Vandenberghe and Peter P De Deyn, and in part genetically by Caroline Van Cauwenberghe,Karolien Bettens and Kristel Sleegers. Research at the Antwerp site is funded in part by the Belgian Science Pol-icy Office Interuniversity Attraction Poles program, the Foundation Alzheimer Research (SAO-FRA), the FlemishGovernment initiated Methusalem Excellence Program, the Research Foundation Flanders (FWO) and the Univer-sity of Antwerp Research Fund, Belgium. KB is a postdoctoral fellow of the FWO. The Antwerp site authors thankthe personnel of the VIB Genetic Service Facility, the Biobank of the Institute Born-Bunge and the Departments ofNeurology and Memory Clinics at the Hospital Network Antwerp and the University Hospitals Leuven.Finish sample collection : Financial support for this project was provided by the Health Research Council of theAcademy of Finland, EVO grant 5772708 of Kuopio University Hospital, and the Nordic Centre of Excellence inNeurodegeneration.Italian sample collections : the Bologna site (FL) obtained funds from the Italian Ministry of research and Univer-sity as well as Carimonte Foundation. The Florence site was supported by grant RF-2010-2319722 , grant fromthe the Cassa di Risparmio di Pistoia e Pescia (Grant 2012) and the Cassa di Risparmio di Firenze (Grant 2012).The Milan site was supported by a grant from the «fondazione Monzino» . We thank the expert contribution ofMr. Carmelo Romano. The Roma site received financial support from Italian Ministry of Health, Grant RF07-08and RC08-09-10-11-12. The Pisa site is grateful to Dr Annalisa LoGerfo for her technical assistance in the DNApurification studies.Spanish sample collection : the Madrid site (MB) was supported by grants of the Ministerio de Educación y Cienciaand the Ministerio de Sanidad y Consumo (Instituto de Salud Carlos III), and an institutional grant of the FundaciónRamón Areces to the CBMSO. We thank I. Sastre and Dr. A Martínez-García for the preparation and control ofthe DNA collection, and Drs. P. Gil and P. Coria for their cooperation in the cases/controls recruitment. We aregrateful to the Asociación de Familiares de Alzheimer de Madrid (AFAL) for continuous encouragement and help.

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Swedish sample collection : Financially supported in part by the Swedish Brain Power network, the Marianne andMarcus Wallenberg Foundation, the Swedish Research Council (521-2010-3134), the King Gustaf V and QueenVictoria’s Foundation of Freemasons, the Regional Agreement on Medical Training and Clinical Research (ALF)between Stockholm County Council and the Karolinska Institutet, the Swedish Brain Foundation and the SwedishAlzheimer Foundation.

CHARGEAGES: The AGES-Reykjavik Study is funded by NIH contract N01-AG-12100 (NIA with contributions from theNEI, NIDCD and NHLBI), the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association),and the Althingi (the Icelandic Parliament).ASPS/PRODEM: The Austrian Stroke Prevention Study and The Prospective Dementia Register of the AustrianAlzheimer Society was supported by The Austrian Science Fond (FWF) grant number P20545-P05 (H. Schmidt)and P13180; The Austrian Alzheimer Society; The Medical University of Graz. Cardiovascular Health Study(CHS): This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C,N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, andHHSN268200960009C; and NHLBI grants HL080295, HL087652, HL105756 with additional contribution fromthe National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided throughAG023629, AG15928, AG20098, AG027058 and AG033193 (Seshadri) from the National Institute on Aging(NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi. Theprovision of genotyping data was supported in part by the National Center for Advancing Translational Sci-ences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Dia-betes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Cen-ter.Framingham Heart Study (FHS): This work was supported by the National Heart, Lung and Blood Institute’sFramingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc for genotyping ser-vices (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis(LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston Univer-sity School of Medicine and Boston Medical Center. This study as also supported by grants from the NationalInstitute on Aging: AG08122 and AG033193 (Seshadri). Drs. Seshadri and DeStefano were also supported byadditional grants from the National Institute on Aging: (R01 AG16495; AG031287, AG033040), the National In-stitute of Neurological Disorders and Stroke (R01 NS17950), and the National Heart, Lung and Blood Institute(U01 HL096917, HL093029 and K24HL038444, RC2-HL102419 and UC2 HL103010.Fundació ACE would like to thank patients and controls who participated in this project. This work has beenfunded by the Fundación Alzheimur (Murcia), the Ministerio de Educación y Ciencia (PCT-010000-2007-18),(DEX-580000-2008-4), (Gobierno de España), Corporación Tecnológica de Andalucía (08/211) and Agencia IDEA(841318) (Consejería de Innovación, Junta de Andalucía). We thank to Ms. Trinitat Port-Carbó and her family fortheir generous support of Fundació ACE research programs.The Rotterdam Study: The Rotterdam Study was funded by Erasmus Medical Center and Erasmus University, Rot-terdam; the Netherlands Organization for Health Research and Development; the Research Institute for Diseasesin the Elderly; the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; theEuropean Commission; and the Municipality of Rotterdam; by grants from the Research Institute for Diseases inthe Elderly (014-93-015; RIDE2), Internationale Stichting Alzheimer Onderzoek, Hersenstichting Nederland, theNetherlands Genomics Initiative–Netherlands Organization for Scientific Research (Center for Medical SystemsBiology and the Netherlands Consortium for Healthy Aging), the Seventh Framework Program (FP7/2007-2013),the ENGAGE project (grant agreement HEALTH-F4-2007-201413), MRACE-grant from the Erasmus MedicalCenter, the Netherlands Organization for Health Research and Development (ZonMW Veni-grant no. 916.13.054).ARIC: The Atherosclerosis Risk in Communities Study (ARIC) is carried out as a collaborative study supportedby National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022 and grants R01-HL087641, RC2-HL102419 (Boer-winkle, CHARGE-S), UC2 HL103010, U01-HL096917 (Mosley) and R01-HL093029; NHGRI contract U01-HG004402; and NIH contract HHSN268200625226C and NIA: R01 AG033193 (Seshadri). Infrastructure was

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http://www.chs-nhlbi.org/pi

partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIHRoadmap for Medical Research.

GERADCardiff University was supported by the Wellcome Trust, Medical Research Council (MRC), Alzheimer’s ResearchUK (ARUK) and the Welsh Government. ARUK supported sample collections at the Kings College London, theSouth West Dementia Bank, Universities of Cambridge, Nottingham, Manchester and Belfast. The Belfast groupacknowledges support from the Alzheimer’s Society, Ulster Garden Villages, N.Ireland R&D Office and the RoyalCollege of Physicians/Dunhill Medical Trust. The MRC and Mercer’s Institute for Research on Ageing supportedthe Trinity College group. DCR is a Wellcome Trust Principal Research fellow. The South West Dementia BrainBank acknowledges support from Bristol Research into Alzheimer’s and Care of the Elderly. The Charles WolfsonCharitable Trust supported the OPTIMA group. Washington University was funded by NIH grants, Barnes JewishFoundation and the Charles and Joanne Knight Alzheimer’s Research Initiative. Patient recruitment for the MRCPrion Unit/UCL Department of Neurodegenerative Disease collection was supported by the UCLH/UCL Biomed-ical Centre and their work was supported by the NIHR Queen Square Dementia BRU. LASER-AD was funded byLundbeck SA. The Bonn group would like to thank Dr. Heike Koelsch for her scientific support. The Bonn groupwas funded by the German Federal Ministry of Education and Research (BMBF): Competence Network Dementia(CND) grant number 01GI0102, 01GI0711, 01GI0420. The AgeCoDe study group was supported by the GermanFederal Ministry for Education and Research grants 01 GI 0710, 01 GI 0712, 01 GI 0713, 01 GI 0714, 01 GI 0715,01 GI 0716, 01 GI 0717. Genotyping of the Bonn case-control sample was funded by the German centre for Neu-rodegenerative Diseases (DZNE), Germany. The GERAD Consortium also used samples ascertained by the NIMHAD Genetics Initiative. HH was supported by a grant of the Katharina-Hardt-Foundation, Bad Homburg vor derHöhe, Germany. The KORA F4 studies were financed by Helmholtz Zentrum München; German Research Centerfor Environmental Health; BMBF; German National Genome Research Network and the Munich Center of HealthSciences. The Heinz Nixdorf Recall cohort was funded by the Heinz Nixdorf Foundation (Dr. Jur. G.Schmidt,Chairman) and BMBF. Coriell Cell Repositories is supported by NINDS and the Intramural Research Program ofthe National Institute on Aging. We acknowledge use of genotype data from the 1958 Birth Cohort collection,funded by the MRC and the Wellcome Trust which was genotyped by the Wellcome Trust Case Control Consor-tium and the Type-1 Diabetes Genetics Consortium, sponsored by the National Institute of Diabetes and Digestiveand Kidney Diseases, National Institute of Allergy and Infectious Diseases, National Human Genome ResearchInstitute, National Institute of Child Health and Human Development and Juvenile Diabetes Research FoundationInternational. The Nottingham Group (KM) are supported by the Big Lottery. MRC CFAS is part of the consortiumand data will be included in future analyses.

ADGCThe National Institutes of Health, National Institute on Aging (NIH-NIA) supported this work through the follow-ing grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIALOAD, U24 AG026395, R01 AG041797; MIRAGE R01 AG025259; Banner Sun Health Research Institute P30AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173,R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128;Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana Univer-sity, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hos-pital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01AG002219; New York University, P30 AG08051, MO1RR00096, and UL1 RR029893; Northwestern Univer-sity, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; Universityof Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; Universityof California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575,P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of Califor-nia, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; Uni-

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versity of Kentucky, P30 AG028383; University of Michigan, P50 AG008671; University of Pennsylvania, P30AG010124; University of Pittsburgh, P50 AG005133, AG030653, AG041718; University of Southern Califor-nia, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944,AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University,R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bankat Duke University Medical Center is funded by NINDS grant # NS39764, NIMH MH60451 and by Glaxo SmithKline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded byNIA grant AG034504 to AJM, The Banner Alzheimer’s Foundation, The Johnnie B. Byrd Sr. Alzheimer’s Insti-tute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites:Newcastle Brain Tissue Resource (funding via the Medical Research Council, local NHS trusts and NewcastleUniversity), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Coun-cil), South West Dementia Brain Bank (funding via numerous sources including the Higher Education FundingCouncil for England (HEFCE), Alzheimer’s Research Trust (ART), BRACE as well as North Bristol NHS TrustResearch and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sourcesincluding Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, InternationalParkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Pa-tologica, Universitat de Barcelona. Marcelle Morrison-Bogorad, PhD., Tony Phelps, PhD and Walter Kukull PhDare thanked for helping to co-ordinate this collection. ADNI Funding for ADNI is through the Northern Califor-nia Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG,Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, Glaxo-SmithKline, Innogenetics, Johnson and Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., NovartisAG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer’s Association, Alzheimer’s DrugDiscovery Foundation, the Dana Foundation, and by the National Institute of Biomedical Imaging and Bioengi-neering and NIA grants U01 AG024904, RC2 AG036535, K01 AG030514. Data collection and sharing for thisproject was funded by the ADNI (National Institutes of Health Grant U01 AG024904). ADNI is funded by the Na-tional Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generouscontributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; BioClinica,Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Com-pany; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.;IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceu-tical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRxResearch; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and TakedaPharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinicalsites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health(www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and thestudy is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego.ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles.This research was also supported by NIH grants P30 AG010129 and K01 AG030514. We thank Drs. D. StephenSnyder and Marilyn Miller from NIA who are ex-officio ADGC members. Support was also from the Alzheimer’sAssociation (LAF, IIRG-08-89720; MP-V, IIRG-05-14147) and the US Department of Veterans Affairs Adminis-tration, Office of Research and Development, Biomedical Laboratory Research Program. P.S.G.-H. is supported byWellcome Trust, Howard Hughes Medical Institute, and the Canadian Institute of Health.

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